ACM named Andrea Goldsmith of Stanford University the 2018-2019 Athena Lecturer for contributions to the theory and practice of adaptive wireless communications, and for the successful transfer of research to commercial technology. Goldsmith introduced innovative approaches to the design, analysis and fundamental performance limits of wireless systems and networks. Her efforts helped develop technologies used in long-term evolution (LTE) cellular devices as well as the Wi-Fi standards that are used in wireless local area networks. Goldsmith participated in the launch of companies to commercialize her work, which has led to the adoption of her ideas throughout the communications industry.

Initiated in 2006 by the ACM Council on Women in Computing (ACM-W), the Athena Lecturer Award celebrates women researchers who have made fundamental contributions to computer science. The award carries a cash prize of $25,000, with financial support provided by Google.

“The anytime, anywhere computing era in which we now live owes a debt to innovators like Andrea Goldsmith who have helped lay the groundwork for the wireless infrastructure that makes mobile  computing possible,” said ACM President Vicki L. Hanson. “Her work has improved the transmission, reception and overall quality of wireless communications. Importantly, Goldsmith’s career has exemplified the spirit of the ACM Athena Lecturer Award in the numerous ways she has mentored young women throughout her career. She has helped prepare promising young women PhD students and postdocs for faculty positions, and she has worked to develop actionable strategies to improve the climate, recruitment and retention of women in the high tech industry.”

Adaptive MIMO
Beginning in the early 1990s, Goldsmith developed several fundamental capacity results for wireless systems. Understanding the Shannon capacity limits of these systems can lead to benefits including increased data rates and extended range while lessening the impact of ongoing challenges in wireless communications including co-channel interference, poor reception, and outages. Goldsmith was the first to propose and develop the underlying theory for time-varying adaptive modulation, as well as new multiple input/multiple output (MIMO) techniques that have been employed throughout the field to improve network capacity and performance.

She proposed techniques, including design of modulation and coding scheme (MCS) tables and quadrature amplitude modulation (MQAM and code) indexed by signal noise radio (SNR) bands, that are used in a variety of wireless systems including EDGE, Wi-Fi and 3GPP/LTE.

Quantenna
In 2005, Goldsmith founded Quantenna Communications to build a product and company around her research in adaptive MIMO wireless. In 2008, as CTO, she led the development of the world’s first 4x4 adaptive MIMO 802.11n Wi-Fi chipset. Compared with other Wi-Fi products on the market, the Quantenna chipset provided better data rates, coverage and reliability and was especially effective for wireless distribution of multiple HD video streams. Today Quantenna products are used by major carriers including AT&T, DirectTV, Comcast, France Telecom, Swisscom and Telefonica.

Biographical Background
Andrea Goldsmith is the Stephen Harris Professor in the School of Engineering at Stanford University. She co-founded and served as Chief Technical Officer of Plume Wi-Fi and of Quantenna, and she currently serves on the corporate or technical advisory boards of Crown Castle Inc., Interdigital Corp., Sequans, Quantenna and Cohere.

Goldsmith has published 160 journal papers, 320 peer-reviewed conference papers, and three textbooks, one of which has been translated into Chinese, Japanese and Russian. She also holds 29 patents, with three pending. Goldsmith is a member of the National Academy of Engineering and the American Academy of Arts and Sciences, and is a Fellow of the IEEE and of Stanford. She has received several awards for her work, including the IEEE ComSoc Edwin H. Armstrong Achievement Award, as well as the National Academy of Engineering Gilbreth Lecture Award. Goldsmith received her PhD, MS and BS degrees in Electrical Engineering from the University of California, Berkeley.

The Athena Lecturer is invited to present a lecture at an ACM event. Goldsmith’s Athena Lecture will be delivered at an ACM event later this year. The award is named after Athena, the Greek goddess of wisdom. With her knowledge and sense of purpose, Athena epitomizes the strength, determination, and intelligence of the “Athena Lecturers.”

Goldsmith will formally receive the Athena Lecturer Award at ACM’s annual awards banquet on June 23, 2018 in San Francisco.

ACM named Dina Katabi of the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory (MIT CSAIL) the recipient of the 2017 ACM Prize in Computing for creative contributions to wireless systems. Recognized as one of the most innovative researchers in the field of networking, Katabi applies methods from communication theory, signal processing and machine learning to solve problems in wireless networking. Among her contributions, she is cited for co-authoring several highly influential papers on overcoming interference in wireless networks to improve the flow of data traffic.  And in inventing a device that seems to be lifted out of the pages of science fiction, she and her team pioneered the use of wireless signals in applications that can sense humans behind walls, determine their movements and even surmise their emotional states. These trailblazing human-sensing technologies hold out promise for use in several applications of daily life including helping the house-bound elderly, and perhaps determining survivors within buildings during search and rescue operations.

The ACM Prize in Computing recognizes early-to-mid-career contributions that have fundamental impact and broad implications. The award carries a prize of $250,000. Financial support is provided by an endowment from Infosys Ltd.

“Innovations which help facilitate communications across mobile networks certainly address an important need,” explained ACM President Vicki L. Hanson. “One recent report estimated that worldwide mobile data traffic grew 18-fold between 2011 and 2016. Dina Katabi’s work has contributed to a seamless increase in traffic, as well as the ever-increasing volumes of data that are shared over mobile systems. The official citation for the ACM Prize in Computing cites Katabi’s creative contributions because she is known for reimagining longstanding challenges in original ways.”

“Infosys is proud to support the ACM Prize in Computing, which this year honors Dina Katabi for her groundbreaking achievements in mobile systems,” said Salil S. Parekh, CEO of Infosys. “By 2020, experts predict that there will be 11.6 billion mobile-connected devices in the world. Our use of these devices, and the underlying networks that they rely upon, will play an increasingly important role in every aspect of life—from the way we communicate with friends and family, to our jobs, to the health of the world economy. By recognizing Katabi’s contributions, we educate the public about the technologies they use every day but may take for granted. Hopefully, we might also inspire the next generation to work in this exciting and very impactful area of computing science and practice.” 

Wireless Network Coding
Wired networks simply route (or forward) signals from one point to another, and early wireless networks were based on this blueprint. Wireless networks, however, are fundamentally different from wired networks and at times face challenges including inadequate mobile support, dead spots, and low throughput—or the amount of data that can be moved from one point to another in a given time. As wireless technology developed, many proposed a new unifying design paradigm called network coding in which each node in a network would perform some computation. At each node, the transmission could be mixed (encoded), or re-mixed (re-encoded), in order to be unmixed (decoded) at its final destination. Katabi was a leader in presenting ideas to make the theory of network coding practical as a way to improve network performance. The papers in which she introduced concrete methods to make network coding practical received awards at major conferences and remain staples of the reading lists in wireless classes.

Interference Mitigation
Following up on her work in network coding, Katabi and her collaborators have written several research papers on the fundamental problem of interference in wireless networks, which occurs when multiple nodes transmit concurrently. In these papers, she modeled how wireless signals mix in the air as code, and then outlined algorithms that allow the receiver to decode these interference-based codes. Katabi’s methods were not only shown to overcome interference in wireless transmissions, but in some instances can be exploited to increase the amount of data that can move over the network.

Sensing and Wireless Signals
At ACM SIGCOMM 2013, Katabi presented a highly influential paper, “See through Walls with Wi-Fi!” She demonstrated how Wi-Fi-based devices and their variants can be used to detect people behind walls, their movements, and even their emotional states. The device works by transmitting wireless radio signals that traverse a wall and reflect off a person’s body back to the device. While the data that comes back from these reflections is very minimal, Katabi and her team developed a series of algorithms that separate the meaningful signals from the random noise produced by the walls and other reflections. The technology can identify a person’s silhouette and detect gestures as subtle as the rise and fall of a person’s chest from the other side of a house. Her lab has recently advanced the technology to remotely monitor a person’s heart rate and other vital signs, to infer, among other indicators, their emotional states. The work has generated a huge amount of interest and was one of the invited demonstrations at President Obama’s White House Demo Day.

Sparse Fast Fourier Transform
In computing, the Discrete Fourier Transform (DFT) is a mathematical technique that is used for processing streams of data in a range of computational tasks including audio/image processing, biochemistry, astronomy, and even GPS. Traditionally, the Fast Fourier Transform (FFT) was the algorithm that was used to process data for a wide range of computational tasks. Katabi, along with MIT colleague Piotr Indyk and students, developed a new algorithm, the Sparse Fast Fourier Transform (SFFT) that processes data 10 to 100 times faster than the FFT. Among its many other benefits, Katabi’s faster transform means that computers need less power to process the same amount of data.

Background
A native of Damascus, Syria, Dina Katabi is the Andrew and Erna Viterbi Professor of Computer Science and Director of the Center for Wireless Networks and Mobile Computing at the Massachusetts Institute of Technology (MIT). She received a PhD and MS in Computer Science from MIT, and a BS in Electrical Engineering from Damascus University, Syria.

Katabi is the author or co-author of over 100 scholarly publications covering a wide range of topics in networks and data communications. Her papers have been cited more than 20,000 times by researchers. She has been recognized with several honors including a MacArthur Fellowship, the ACM Grace Murray Hopper Award, several ACM SIGCOMM Best Paper Awards, an ACM SIGCOMM Test of Time Award and a National Science Foundation Career Award. Katabi is an ACM Fellow and was elected to the National Academy of Engineering.

ACM will present the 2017 ACM Prize in Computing at its annual Awards Banquet on June 23, 2018 in San Francisco, California.

ACM named John L. Hennessy, former President of Stanford University, and David A. Patterson, retired Professor of the University of California, Berkeley, recipients of the 2017 ACM A.M. Turing Award for pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry. Hennessy and Patterson created a systematic and quantitative approach to designing faster, lower power, and reduced instruction set computer (RISC) microprocessors. Their approach led to lasting and repeatable principles that generations of architects have used for many projects in academia and industry. Today, 99% of the more than 16 billion micro-processors produced annually are RISC processors, and are found in nearly all smartphones, tablets, and the billions of embedded devices that comprise the Internet of Things (IoT).

Hennessy and Patterson codified their insights in a very influential book, Computer Architecture: A Quantitative Approach, now in its sixth edition, reaching generations of engineers and scientists who have adopted and further developed their ideas. Their work underpins our ability to model and analyze the architectures of new processors, greatly accelerating advances in microprocessor design.

The ACM Turing Award, often referred to as the “Nobel Prize of Computing,” carries a $1 million prize, with financial support provided by Google, Inc. It is named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing.

“ACM initiated the Turing Award in 1966 to recognize contributions of lasting and major technical importance to the computing field,” said ACM President Vicki L. Hanson. “The work of Hennessy and Patterson certainly exemplifies this standard. Their contributions to energy-efficient RISC-based processors have helped make possible the mobile and IoT revolutions. At the same time, their seminal textbook has advanced the pace of innovation across the industry over the past 25 years by influencing generations of engineers and computer designers.”

Attesting to the impact of Hennessy and Patterson’s work is the assessment of Bill Gates, principal founder of Microsoft Corporation, that their contributions “have proven to be fundamental to the very foundation upon which an entire industry flourished.”

Development of MIPS and SPARC
While the idea of reduced complexity architecture had been explored since the 1960s—most notably in the IBM 801 project—the work that Hennessy and Patterson led, at Stanford and Berkeley respectively, is credited with firmly establishing the feasibility of the RISC approach, popularizing its concepts, and introducing it to academia and industry. The RISC approach differed from the prevailing complex instruction set computer (CISC) computers of the time in that it required a small set of simple and general instructions (functions a computer must perform), requiring fewer transistors than complex instruction sets and reducing the amount of work a computer must perform.

Patterson’s Berkeley team, which coined the term RISC, built and demonstrated their RISC-1 processor in 1982. With 44,000 transistors, the RISC-1 prototype outperformed a conventional CISC design that used 100,000 transistors. Hennessy co-founded MIPS Computer Systems Inc. in 1984 to commercialize the Stanford team’s work. Later, the Berkeley team’s work was commercialized by Sun Microsystems in its SPARC microarchitecture.

Despite initial skepticism of RISC by many computer architects, the success of the MIPS and SPARC entrepreneurial efforts, the lower production costs of RISC designs, as well as more research advances, led to wider acceptance of RISC. By the mid-1990s, RISC microprocessors were dominant throughout the field.

Groundbreaking Textbook
Hennessy and Patterson presented new scientifically-based methodologies in their 1990 textbook Computer Architecture: a Quantitative Approach. The book has influenced generations of engineers and, through its dissemination of key ideas to the computer architecture community, is credited with significantly increasing the pace of advances in microprocessor design. In Computer Architecture, Hennessy and Patterson encouraged architects to carefully optimize their systems to allow for the differing costs of memory and computation. Their work also enabled a shift from seeking raw performance to designing architectures that take into account issues such as energy usage, heat dissipation, and off-chip communication. The book was groundbreaking in that it was the first text of its kind to provide an analytical and scientific framework, as well as methodologies and evaluation tools for engineers and designers to evaluate the net value of microprocessor design.

Biographical Background

John L. Hennessy
John L. Hennessy was President of Stanford University from 2000 to 2016. He is Director of the Knight-Hennessy Scholars Program at Stanford, a member of the Board of Cisco Systems and the Gordon and Betty Moore Foundation and Chairman of the Board of Alphabet Inc. Hennessy earned his Bachelor’s degree in electrical engineering from Villanova University and his Master’s and doctoral degrees in computer science from the State University of New York at Stony Brook.

Hennessy’s numerous honors include the IEEE Medal of Honor, the ACM-IEEE CS Eckert-Mauchly Award (with Patterson), the IEEE John von Neumann Medal (with Patterson), the Seymour Cray Computer Engineering Award, and the Founders Award from the American Academy of Arts and Sciences. Hennessy is a Fellow of ACM and IEEE, and is a member of the National Academy of Engineering, the National Academy of Sciences and the American Philosophical Society.

David A. Patterson
David A. Patterson is a Distinguished Engineer at Google and serves as Vice Chair of the Board of the RISC-V Foundation, which offers an open free instruction set architecture with the aim to enable a new era of processor innovation through open standard collaboration. Patterson was Professor of Computer Science at UC, Berkeley from 1976 to 2016. He received his Bachelor’s, Master’s and doctoral degrees in computer science from the University of California, Los Angeles.

Patterson’s numerous honors include the IEEE John von Neumann Medal (with Hennessy), the ACM-IEEE CS Eckert-Mauchly Award (with Hennessy), the Richard A. Tapia Award for Scientific Scholarship, Civic Science, and Diversifying Computing, and the ACM Karl V. Karlstrom Outstanding Educator Award. Patterson served as ACM President from 2004 to 2006. He is a Fellow of ACM, AAAS and IEEE, and was elected to the National Academy of Engineering and the National Academy of Sciences.

ACM will present the 2017 ACM A.M. Turing Award at its annual Awards Banquet on June 23, 2018 in San Francisco, California.

The winners of the 2017-2018 Cutler-Bell Prize in High School Computing were announced by ACM and the Computer Science Teachers Association (CSTA). Five high school students were selected from among a pool of graduating high school seniors throughout the US. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize winner receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed. This year’s Cutler-Bell Prize recipients will be formally recognized at the Computer Science Teachers Association’s annual conference, July 7-10, 2018 in Omaha, Nebraska.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Sreya Guha, Castilleja School, Palo Alto, California
Sreya Guha’s “Related Fact Checks” service was built to combat fake news by connecting information written in articles to the related fact(s) on fact checking websites. The tool does not label articles as either fact or fiction, since many articles contain both; but instead, it provides relevant fact checks related to an article being read. A browser extension allows the service to be accessible to a wide audience with the hopes of slowing the tide of fake news. Facing the challenge of the abundance of fake news, Guha realized through her research that most fake news stories tend to stick to a small number of themes (anti-vaccine, anti-climate change etc.). Even in the absence of a fact check for a particular claim, giving the reader a fact check within the same theme can help them critically understand the story they are reading.

Amir Helmy, Eastside High School, Gainesville, Florida
Amir Helmy developed the Seizario app, “a mobile application designed to aid epileptic patients, their families and caregivers in managing their daily lives effectively, using smartphones. Seizario aims to offer two main features; automatic detection of several emergency scenarios, and easy and immediate communication of critical information to family members and caregivers.” Using an accelerometer-based classification algorithm, Seizario detects seizures and harmful falls. When detected, warning and alert messages are triggered and sent to pre-identified recipients with time, location, and activity. The app also records detailed log entries that can be used by caregivers and medical professionals for analysis and treatment improvement. By using smartphone technology, the potential for reaching more of the population vulnerable to seizures and falls is increased and the offers improved self-management and reduced response times.

Amy Jin, The Harker School, San Jose, California
Amy Jin is using computer vision to evaluate surgical skill and “provide individualized feedback and training to surgeons.” This computer vision “coach” analyzes surgical performance through tool movements and usage patterns to reflect surgical skill and technique. By feeding surgical videos through her computational pipeline Jin has automated surgical skill assessment, focusing on efficiency, motion economy, and bimanual dexterity as areas of examination, in order to provide surgeons with information on how to improve their surgical technique and performance. Assessment results were validated by a team of surgeons. This work sets the stage for “building a context-aware system” to provide surgeons with targeted feedback and training to improve their surgical performance.

Benjamin Spector and Michael Truell, Horace Mann School, Bronx, New York
Submitting as a team, Benjamin Spector and Michael Truell created Halite, an online programming competition. Halite is now in its second iteration and is one of the largest limited-time programming competitions with more than 5,500 users over the course of the two competition runs. Starting with the goal of producing an open-source platform and game where “anyone could easily program a bot, but would also have the depth to support and interest experienced programmers,” Spector and Truell set ambitious requirements for the system, game, and competition desiring a visually appealing, secure, scalable, beginner-friendly, but difficult to solve, multi-faceted competition that would allow the user to write code in any language, test and visualize their bots locally, and once uploaded, would play against other bots in real time and the user would receive performance feedback in real time. Halite has successfully allowed thousands of users, mostly university and high school students some of whom have never programmed before, the opportunity to learn new skills ranging from programming languages to machine learning. The collaborative environment encouraged by Halite, and its creators, has had a tangible impact on computer science education through gamification.

“We are proud to support an effort which encourages high school computer science students to develop projects that will advance society,” said Cutler and Bell. “ We hope that, whatever careers these students ultimately pursue, they will consider the ways in which technology can have a positive impact on the wider world. Beyond challenging the students to stretch their skills and imaginations, developing their own projects gives students confidence.”

“I always enjoy reading about the Cutler-Bell Prize-winning projects and the surprising technologies the students have envisioned to solve a problem in society or business,” says ACM President Vicki L. Hanson. “ACM has long championed the idea that integrating computer science education throughout the K-12 curriculum fosters computational thinking—or a new way of seeing the world. The Cutler-Bell Prize-winning projects are excellent examples of computational thinking in action. ACM thanks Gordon Bell and David Cutler, our partners at the CSTA, and the computer science teachers who have guided and inspired this year’s Cutler-Bell Prize recipients.”

“I am so impressed by the winning student projects, and the many other high quality submissions we received this year. The winning projects are examples of the novel solutions to real world problems that students create when they have access to a high quality computer science education,” said Jake Baskin, Executive Director of the Computer Science Teachers Association. “I can’t wait to see the explosion in new ideas as the number of K-12 students learning computer science continues to increase.”

For more information about the ACM/CSTA Cutler-Bell Prize in High School Computing, visit http://awards.acm.org/cutler-bell and http://www.csteachers.org/CutlerBell.

ACM has named 54 members ACM Fellows for major contributions in areas including database theory, design automation, information retrieval, multimedia computing and network security. The accomplishments of the 2017 ACM Fellows lead to transformations in science and society. Their achievements play a crucial role in the global economy, as well as how we live and work every day.

"To be selected as a Fellow is to join our most renowned member grade and an elite group that represents less than 1 percent of ACM’s overall membership,” explains ACM President Vicki L. Hanson. “The Fellows program allows us to shine a light on landmark contributions to computing, as well as the men and women whose hard work, dedication, and inspiration are responsible for groundbreaking work that improves our lives in so many ways."

Underscoring ACM’s global reach, the 2017 Fellows hail from universities, companies and research centers in China, Denmark, Germany, Hong Kong, Switzerland, the United Kingdom and the United States.

The 2017 Fellows have been cited for numerous contributions in areas including artificial intelligence, big data, computer architecture, computer graphics, high performance computing, human-computer interaction, sensor networks, and wireless networking.

ACM will formally recognize its 2017 Fellows at the annual Awards Banquet, to be held in San Francisco on June 23, 2018. Additional information about the 2017 ACM Fellows, and the awards event, as well as previous ACM Fellows and award winners, is available on the ACM Awards site.

ACM named a 12-member Chinese team the recipients of the 2017 ACM Gordon Bell Prize for their research project, “18.9-Pflops Nonlinear Earthquake Simulation on Sunway TaihuLight: Enabling Depiction of 18-Hz and 8-Meter Scenarios.” Using the Sunway TaihuLight, which is ranked as the world’s fastest supercomputer, the team developed software that was able to efficiently process 18.9 Pflops (or 18.9 quadrillion calculations per second) of data and create 3D visualizations relating to a devastating earthquake that occurred in Tangshan, China in 1976. The team’s software included innovations that achieved greater efficiency than had been previously attained running similar programs on the Titan and TaihuLight supercomputers.

The ACM Gordon Bell Prize tracks the progress of parallel computing and rewards innovation in applying high performance computing to challenges in science, engineering, and large- scale data analytics. The award was presented today by ACM President Vicki Hanson and Subhash Saini, Chair of the 2017 Gordon Bell Prize Award Committee, during the International Conference for High Performance Computing, Networking, Storage and Analysis (SC17) in Denver, Colorado.

Although earthquake prediction and simulation is an inexact and emerging area of research, scientists hope that the use of supercomputers, which can process vast sets of data to address the myriad of variables at play in geologic events, may lead to better prediction and preparedness. For example, the Chinese team’s 3D simulations may inform engineering standards for buildings being developed in zones known to have seismic activity. In this vein, many have advocated for a significant increase in the amount of sensors to regularly monitor seismic activity. The Tangshan earthquake, which occurred on July 28, 1976 in Tangshan, Hebei, China, is regarded as the most devastating earthquake of the 20^th century, and resulted in approximately 242,000-700,000 deaths. In developing their simulations for the Tangshan earthquake, the winning team included input data from the entire spatial area of the quake, a surface diameter of 320 km by 312 km, as well as 40 km deep below the earth’s surface. The input data also included a frequency range of the earthquake of up to 18 Hz (Hertz). In the study of earthquakes, a Hertz is a unit of measurement that measures the number of times an event happens in the period of a second. For example, it might correspond to the number of times the ground shakes back and forth during an earthquake. Previous simulations of violent earthquakes have employed a lower frequency than 18 Hz, since enormous memory and time consumption are needed for high frequency simulations.

This year’s winning team is not the first to develop algorithms for supercomputers in an effort to simulate earthquake activity. In the abstract of their presentation, the 2017 Gordon Bell recipients write: “Our innovations include: (1) a customized parallelization scheme that employs the 10 million cores efficiently at both the process and thread levels; (2) an elaborate memory scheme that integrates on-chip halo exchange through register communication, optimized blocking configuration guided by an analytic model, and coalesced DMA access with array fusion; (3) on-the-fly compression that doubles the maximum problem size and further improves the performance by 24%."

Of its new innovations, the Chinese team adds that its on-the-fly compression scheme may be effectively applied to other challenges in exascale computing. In their paper, the authors state: “The even more exciting innovation is the on-the-fly compression scheme, which, at the cost of an acceptable level of accuracy lost, scales our simulation performance and capabilities even beyond the machine’s physical constraints. While the current compression scheme is largely customized for our specific application and the Sunway architecture, we believe the idea has great potential to be applied to other applications and other architectures.”

Winning team members include Haohuan Fu, Tsinghua University and National Supercomputing Center, Wuxi, China; Conghui He, Tsinghua University and National Supercomputing Center, Wuxi, China; Bingwei Chen, Tsinghua University and National Supercomputing Center, Wuxi, China; Zekun Yin, Shandong University; Zhenguo Zhang, Southern University of Science and Technology, China; Wenqiang Zhang, University of Science and Technology of China; Tingjian Zhang, Shandong University; Wei Xue, Tsinghua University and National Supercomputing Center, Wuxi, China; Weiguo Liu, Shandong University; Wanwang Yin, National Research Center of Parallel Computer Engineering and Technology, China; Guangwen Yang, Tsinghua University and National Supercomputing Center, Wuxi, China; and Xioafei Chen, Southern University of Science and Technology, China.

Innovations from advanced scientific computing have a far-reaching impact in many areas of science and society—from understanding the evolution of the universe and other challenges in astronomy, to complex geological phenomena, to nuclear energy research, to economic forecasting, to developing new pharmaceuticals. The annual SC conference brings together scientists, engineers and researchers from around the world for an outstanding week of technical papers, timely research posters, and tutorials.

The Sunway TaihuLight is a Chinese supercomputer with over 10.5 M heterogeneous cores and is ranked as the fastest supercomputer in the world.  Located at the National Supercomputer Center in Wuxi, Jingsu, China, it is nearly three times as fast as the Tianhe-2, the supercomputer that previously held the world record for speed.

2017 Members Selected as Pioneering Innovators that Are Advancing the Digital Age

ACM named 43 Distinguished Members for an extraordinary array of achievements, reflecting the many distinct areas of research and practice in the computing and information technology fields.

"Computing technology is becoming an increasingly dominant force in our daily lives and is transforming society at every level,” explains ACM President Vicki L. Hanson. “In naming a new roster of Distinguished Members each year, ACM underscores that the innovations which improve our lives do not come about by accident, but rather are the result of the hard work, inspiration and creativity of leading professionals in the field. We honor the 2017 class of ACM Distinguished Members for the essential role their accomplishments play in how we live and work."

The 2017 ACM Distinguished Members work at leading universities, corporations and research institutions around the world, including Australia, Belgium, Canada, France, Hong Kong, Italy, The Netherlands, Portugal, Qatar, Singapore, South Africa, South Korea, and the United States. These innovators have made contributions in a wide range of technical areas including accessibility, computational geometry, cryptography, computer security, computer science education, data structures, healthcare technologies, human-computer interaction, nanoscale computing, robotics, and software engineering —to name a few.

The Association for Computing Machinery (ACM) and IEEE Computer Society IEEE CS) have named Jesύs Labarta of the Barcelona Supercomputing Center (BSC) and Universitat Politècnica de Catalunya (UPC) as the recipient of the 2017 ACM-IEEE CS Ken Kennedy Award.  Labarta is recognized for his seminal contributions to programming models and performance analysis tools for high performance computing. The award will be presented at SC 17: The International Conference for High Performance Computing, Networking, Storage and Analysis, November 12-17, in Denver, Colorado.

Throughout his career, Labarta has developed tools for scientists and engineers working in parallel programming.  In the programming models area, he made fundamental contributions to the concept of asynchronous task-based models and intelligent runtime systems. With Labarta’s approach, by using pragma directives that specify the region of code that constitutes tasks and the directionality of the data used by them, the programmer has a unified mechanism to allow intelligent runtime systems to detect and exploit concurrency as well as to manage locality. These ideas have been developed by Labarta’s team on the OmpSs model and Nanos runtime.  His team’s work has also enhanced the interoperability between OmpSs (later Open multi-processing (MP)) and message passing interface (MPI).

In the performance tools area, Labarta’s team develops and distributes Open Source Barcelona Supercomputer Center (BSC) tools that are employed throughout the field. These BSC tools are designed to analyze an application’s behavior and identify issues that may impact performance. Paraver, the most widely used BSC tool, is a trace-based performance analyzer that processes and extracts information. Other tools like Dimemas or the Performance Analytics modules developed by Labarta’s team help squeeze relevant insight and perform predictive analyses from the raw performance data captured by the instrumentation packages.

Labarta is Director of the Computer Science Department at the Barcelona Supercomputing Center and a Professor of Computer Architecture at the Universitat Politècnica de Catalunya.  From 1996 to 2004 he served as the Director of the European Center of Parallelism of Barcelona (CEPBA). He has published more than 250 articles in conferences and journals in areas including high performance architectures and systems software.  He has been involved in research and cooperation with many leading companies on HPC-related topics. Currently Labarta is the leader of the Performance Optimization and Productivity EU Center of Excellence where more than 100 users (both academic and SMEs) from a very wide range of application sectors receive performance assessments and suggestions for code refactoring efforts.

ACM and the IEEE Computer Society co-sponsor the Kennedy Award, which was established in 2009 to recognize substantial contributions to programmability and productivity in computing and significant community service or mentoring contributions. It was named for the late Ken Kennedy, founder of Rice University’s computer science program and a world expert on high performance computing. The Kennedy Award carries a US $5,000 honorarium endowed by the SC Conference Steering Committee.

Shaden Smith (University of Minnesota) and Yang You (University of California, Berkeley) are the recipients of the 2017 ACM/IEEE-CS George Michael Memorial HPC Fellowships. Smith is being recognized for his work on efficient and parallel large-scale sparse tensor factorization for machine learning applications. You is being recognized for his work on designing accurate, fast, and scalable machine learning algorithms on distributed systems.

Shaden Smith’s research is in the general area of parallel and high performance computing with a special focus on developing algorithms for sparse tensor factorization. Sparse tensor factorization facilitates the analysis of unstructured and high dimensional data.

Smith has made several fundamental contributions that have already advanced the state of the art on sparse tensor factorization algorithms. For example, he developed serial and parallel algorithms in the area of Canonical Polyadic Decomposition (CPD) that are over five times faster than existing open source and commercial approaches. He also developed algorithms for Tucker decompositions that are up to 21 times faster and require 28 times less memory than existing algorithms. Smith’s algorithms can efficiently operate on systems containing a small number of multi-core/manycore processors to systems containing tens of thousands of cores.

Yang You’s research interests include scalable algorithms, parallel computing, distributed systems and machine learning. As computers increasingly use more time and energy to transfer data (i.e., communicate), the invention or identification of algorithms that reduce communication within systems is becoming increasingly essential. In well-received research papers, You has made several fundamental contributions that reduce the communications between levels of a memory hierarchy or between processors over a network.

In his most recent work, “Scaling Deep Learning on GPU and Knights Landing Clusters,” You’s goal is to scale up the speed of training neural networks so that networks which are relatively slow to train can be redesigned for high performance clusters. This approach has reduced the percentage of communication from 87% to 14% and resulted in a five-fold increase in speed.

The ACM/IEEE-CS George Michael Memorial HPC (GMM) Fellowship is endowed in memory of George Michael, one of the founding fathers of the SC Conference series. The fellowship honors exceptional PhD students throughout the world whose research focus is on high performance computing applications, networking, storage or large-scale data analytics using the most powerful computers that are currently available. The Fellowship includes a $5,000 honorarium and travel expenses to attend SC17 in Denver Colorado, November 12-17, 2017, where the GMM Fellowships will be formally presented.

Moshe Y. Vardi, the Karen Ostrum George Distinguished Service Professor in Computational Engineering and Director of the Ken Kennedy Institute for Information Technology at Rice University, is the recipient of the 2017 ACM Presidential Award. Vardi is recognized for building Communications of the ACM, the Association for Computing Machinery’s flagship publication, into the computing field’s preeminent print and online magazine.

Communications of the ACM was established in 1958 and today has a worldwide circulation of nearly 100,000. Though always a respected computing publication, by the time Vardi became editor in July, 2008, many came to believe that Communications’ editorial content had drifted away from the core interests of the ACM community. Leading Communications' editorial board and staff, Vardi broadened the magazine’s editorial focus to offer a truly global view of the computing community. Communications rapidly became a “must-read,” known for its industry news, insightful and biting commentary, analyses of real-world applications, historic technology overviews, and in-depth articles on computing research that are accessible to a broad-based audience.

“Communications is the main vehicle ACM uses to share with the world the excitement of working in this field,” explained Hanson. “The magazine also serves as a public square in which ACM members from different disciplines and regions read about the most recent developments in computing, offer their viewpoints and stay connected. During his tenure, Moshe has transformed Communications of the ACM into a publication that is essential, accessible and enjoyable."

In addition to strengthening the content of the publication, Vardi is cited for leveraging the latest technologies to expand the magazine’s worldwide audience. He initiated and oversaw the development of the Communications website, digital edition and mobile apps— all of which have significantly increased the magazine’s readership and influence.

The late Charles P. “Chuck” Thacker was named recipient of the ACM - IEEE CS Eckert-Mauchly Award for fundamental networking and distributed computing contributions including Ethernet, the Xerox Alto, and development of the first tablet computers. Often hailed as an “engineer’s engineer,” Thacker made fundamental contributions across the full breadth of computer development, from analog circuit and power supply design to logic design, processor and network architecture, system software, languages, and applications.

In 1970, Xerox opened its Palo Alto Research Center (PARC) and hired several leading computer scientists and engineers, including Thacker. Early on, the staff at Xerox PARC was using a time-sharing approach in which various terminals were connected to a single computer. Because time sharing was a slow and cumbersome process, leaders at Xerox PARC conceived the idea of developing personal computers as part of a network that would be used for communication as well as computation.

Mainframe computers in the early 1970s were so large that they took up whole rooms, and their expense made them relatively scarce. Under the paradigm at the time, computer architecture needed to be either scaled up (more hardware) for better performance, or scaled down (less hardware) for lower cost. Thacker realized that a personal computer would need to be designed differently from a standard computer to address space constraints, maintain strong performance, and be inexpensive if it was to become pervasive.

At the same time, the idea of a “personal” computer that would be geared more toward human-paced activities called for the engineers to prioritize input/output (I/O) functions rather than application functions, as had traditionally been the case.

The new design feature Thacker employed as the Lead Engineer in what would become the Xerox Alto Computer was a central processing unit (CPU) microprocessor that used microcode for most of the computer’s I/O functions, rather than hardware. The microcode controlled various tasks, including executing the normal instruction set, memory refresh, and network and display functions. The Xerox Alto was therefore not simply a mini-version of existing computers, but had a novel architecture that allowed it to deploy new kinds of software.

Today the Alto is recognized as being the first modern personal computer. The initial architecture of the Alto gave rise to other important inventions developed by engineers at Xerox PARC including WYSIWIG (What You See Is What You Get) editing, laser printing, drawing and painting, email, mouse-driven graphical user interfaces, and many other features that are commonplace in personal computers today.

Another critical innovation of Thacker’s that was an outgrowth of his work on the Alto was the development of hardware for Bob Metcalfe’s invention of the Ethernet Local Area Network (LAN), which facilitated communication among computers.

Twenty years after the development of the Xerox Alto, Thacker made another foundational contribution to personal computing with the development of the Lectrice, a laboratory prototype for today’s portable PCs. He went on to develop a prototype upon which Microsoft Tablet PC software was developed, as well as a system for reading electronic books that laid the groundwork for many of today’s e-readers. One of Thacker’s most recent contributions is the design of AN3, a low-cost, efficient circuit-switched data center network.

The ACM - IEEE CS Eckert-Mauchly Award is known as the computer architecture community’s most prestigious award. ACM and IEEE Computer Society co-sponsor the award, which was initiated in 1979. It recognizes contributions to computer and digital systems architecture and comes with a $5,000 prize. The award was named for John Presper Eckert and John William Mauchly, who collaborated on the design and construction of the Electronic Numerical Integrator and Computer (ENIAC), the pioneering large-scale electronic computing machine, which was completed in 1947.

Haitham Hassanieh is the recipient of the ACM 2016 Doctoral Dissertation Award. Hassanieh developed highly efficient algorithms for computing the Sparse Fourier Transform, and demonstrated their applicability in many domains including networks, graphics, medical imaging and biochemistry.  In his dissertation, The Sparse Fourier Transform: Theory and Practice, he presented a new way to decrease the amount of computation needed to process data, thus increasing the efficiency of programs in several areas of computing.

In computer science, the Fourier transform is a fundamental tool for processing streams of data. It identifies frequency patterns in the data, a task that has a broad array of applications. For many years, the Fast Fourier Transform (FFT) was considered the most efficient algorithm in this area. With the growth of Big Data, however, the FFT cannot keep up with the massive increase in datasets. In his doctoral dissertation Hassanieh presents the theoretical foundation of the Sparse Fourier Transform (SFT), an algorithm that is more efficient than FFT for data with a limited number of frequencies. He then shows how this new algorithm can be used to build practical systems to solve key problems in six different applications including wireless networks, mobile systems, computer graphics, medical imaging, biochemistry and digital circuits. Hassanieh’s Sparse Fourier Transform can process data at a rate that is 10 to 100 times faster than was possible before, thus greatly increasing the power of networks and devices.

Hassanieh is an Assistant Professor in the Department of Electrical and Computer Engineering and the Department of Computer Science at the University of Illinois at Urbana-Champaign. He received his MS and PhD in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT). A native of Lebanon, he earned a BE in Computer and Communications Engineering from the American University of Beirut. Hassanieh’s Sparse Fourier Transform algorithm was chosen by MIT Technology Review as one of the top 10 breakthrough technologies of 2012. He has also been recognized with the Sprowls Award for Best Dissertation in Computer Science, and the SIGCOMM Best Paper Award.

Honorable Mention for the 2016 ACM Doctoral Dissertation Award went to Peter Bailis of Stanford University and Veselin Raychev of ETH Zurich.

In Bailis’s dissertation, Coordination Avoidance in Distributed Databases, he addresses a perennial problem in a network of multiple computers working together to achieve a common goal: Is it possible to build systems that scale efficiently (process ever-increasing amounts of data) while ensuring that application data remains provably correct and consistent? These concerns are especially timely as Internet services such as Google and Facebook have led to a vast increase in the global distribution of data. In addressing this problem, Bailis introduces a new framework, invariant confluence, that mitigates the fundamental tradeoffs between coordination and consistency. His dissertation breaks new conceptual ground in the areas of transaction processing and distributed consistency—two areas thought to be fully understood. Bailis is an Assistant Professor of Computer Science at Stanford University. He received a PhD in Computer Science from the University of California, Berkeley and his AB in Computer Science from Harvard College.

Raychev’s dissertation, Learning from Large Codebases, introduces new methods for creating programming tools based on probabilistic models of code that can solve tasks beyond the reach of current methods. As the size of publicly available codebases has grown dramatically in recent years, so has interest in developing programming tools that solve software tasks by learning from these codebases. Raychev’s dissertation takes a novel approach to addressing this challenge that combines advanced techniques in programming languages with machine learning practices. In the thesis, Raychev lays out four separate methods that detail how machine learning approaches can be applied to program analysis in order to produce useful programming tools. These include: code completion with statistical language models; predicting program properties from big code; learning program from noisy data; and learning statistical code completion systems. Raychev’s work is regarded as having the potential to open up several promising new avenues of research in the years to come. Raychev is currently a co-founder and Chief Technology Officer of DeepCode, a company developing artificial intelligence-based programming tools. He received a PhD in Computer Science from ETH Zurich. A native of Bulgaria, he received MS and BS degrees from Sofia University.

Leonard Jay Shustek was named recipient of the ACM Distinguished Service Award for the establishment and success of the Computer History Museum, the world’s leading institution in exploring the history of computing and its impact on society.  Shustek has helped bring to the world the story of how the greatest innovation of our time has come to be. In 1995, after retiring from the network diagnostic company he co-founded, Shustek began teaching computer architecture at Stanford University. He soon realized that students were as interested in computer history as they were in computer architecture. Instead of returning to Stanford, he began a quest that would ultimately lead him to acquire a group of artifacts from The Computer Museum in Boston, with an eye toward forming a new computer history museum in the heart of Silicon Valley.

Today, thanks to the leadership, vision and tenacity of Shustek, the Computer History Museum (CHM) is acknowledged as the world’s most important museum chronicling the rise of computing and its impact on society. With a staff of 75 serving 200,000 visitors each year, CHM has realized Shustek’s founding goal of an organization that would be “built to last.” CHM is housed in a complex comprised of a 119,000-square-foot building for exhibits and hands-on labs; a 25,000-square-foot climate-controlled warehouse for papers and artifacts; and a new 50,000-square-foot research center for scholars and archival work. Throughout the museum’s growth and development, Shustek has engaged in a range of activities, from leading the museum in raising $125 million to tracking down vintage code related to operating systems no longer in use.

For the general public, signature exhibitions like “Revolution” translate the history of computing into an experience that the average person can not only appreciate, but enjoy. For the computing field, CHM’s role as the world’s major repository of artifacts and historic preservation allows innovators to access the past, in order to move into the future.

The ACM Distinguished Service Award is presented on the basis of value and degree of services to the computing community. The contribution should not be limited to service to the Association, but should include activities in other computer organizations and should emphasize contributions to the computing community at large.

Owen Astrachan was named recipient of the Karl V. Karlstrom Outstanding Educator Award for three decades of innovative computer science pedagogy and inspirational community leadership in broadening the appeal of high school and college introductory computer science courses. Astrachan, a Professor at Duke University, is known as “Mr. AP” because of the central role he has played in the Advanced Placement Computer Science exam taken by high school students. From 1985 to 1989, he served on the committee that writes the AP CS exam, and from 1989 to 1994 he was the Chief Reader, the person in charge of grading the exam. Over his three decades of involvement, Astrachan also played a critical role as the exam’s language changed from Pascal to C++, and later to Java, the language it is given in today.

His broad knowledge of the field, and the respect he garnered within the computer science education community, made him a natural candidate to be the Principal Investigator (project lead), in a 10-year National Science Foundation-funded effort to develop an AP CS Principles course and exam. An important goal of the AP CS Principles exam is to encourage participation in computer science by traditionally underrepresented student communities. The first AP CS Principles courses were offered in the fall of 2016 and the first exam was administered on May 5, 2017 to over 50,000 students— the largest first-year AP exam administration ever.

Astrachan has also made important contributions in several other areas of computer science pedagogy at the K-12/pre-college and college level. Many regard Tapestry, his introductory textbook for C++, as one of the best in the field. His extensive publications and talks on subjects ranging from object-oriented programming to software engineering instruction have also been highly influential. His role in advancing understanding computer science at every level has been strongly influenced by the community of students, teachers, and educators from whom he has learned and with whom he has shared so much.

The Karl V. Karlstrom Outstanding Educator Award is presented annually to an outstanding educator who is appointed to a recognized educational baccalaureate institution.  The recipient is recognized for advancing new teaching methodologies; effecting new curriculum development or expansion in Computer Science and Engineering; or making a significant contribution to the educational mission of ACM. Those with 10 years or less teaching experience are given special consideration. A prize of $10,000 is supplied by Pearson Education.

Ken Banks was named recipient of the Eugene L. Lawler Award for developing FrontlineSMS, using mobile technology and text messaging to empower people to share information, organize aid, and reconnect communities during crises. A self-described “mobile anthropologist,” Banks has a gift for building technology that benefits humanity. As someone who was writing code and tinkering with computers since he was 13, Banks instinctively saw an opportunity to harness the world’s most-used communication platform—mobile messaging—to help people in the developing world.  In 2005, he designed, coded and launched FrontlineSMS, a mobile messaging platform that allows people to subscribe to groups, receive alerts, and establish communication hubs. FrontlineSMS played an important role in the 2007 Nigerian presidential election, where it was used to monitor, identify and curtail violence and harassment at polling places. Because of FrontlineSMS’s built-in flexibility, it quickly became a standard platform deployed in 170 countries by countless organizations. It has been used to help family farmers in Laos, train rural medics in Ecuador, double the amount of patients receiving tuberculosis care in Malawi, and monitor disease outbreaks across Africa. 

Banks continues his work as an Entrepreneur-in-Residence at CARE International. To achieve CARE’s goal of raising more people above the $2 per day extreme poverty level, Banks is leading the development of a new mobile phone application for Village Savings and Loan Associations. Along with his colleagues at CARE, he is also investigating how technology might be used to advance gender equality in Rwanda. His two books The Rise of the Reluctant Innovator and Social Entrepreneurship and Innovation recount his experiences—and those of other global social innovators— and serve as guides for those who are inspired to leverage technology for positive social change.

The Eugene L. Lawler Award for Humanitarian Contributions within Computer Science and Informatics recognizes an individual or group who has made a significant contribution through the use of computing technology. It is given once every two years, assuming that there are worthy recipients. The award is accompanied by a prize of $5,000.

Valerie Barr was named recipient of the Outstanding Contribution to ACM Award for reinventing ACM-W, increasing its effectiveness in supporting women in computing worldwide and encouraging participation in ACM. Barr, a Professor at Union College, has been uniquely effective in turning good ideas about how to increase the participation of women in computing into tangible programs that yield measurable results.  When she first joined the Association for Computing Machinery’s Council on Women in Computing (ACM-W) in 2005, she launched a scholarship program. Barr and others believed that if more young women could attend major computer research conferences, they would be encouraged to continue in the field. Since its inception in 2006, the program has expanded the horizons of numerous young women internationally and has continued to grow. Because of Barr’s adeptness at conveying her vision to funders, the program is 100% supported by industry contributions. Last year, the ACM-W Scholarship Program distributed $40,000 over 40 awards.

ACM-W’s dedicated and hard-working volunteers share a central goal of bringing women together for mentoring, networking, and other career-enhancing activities. Since becoming the Chair of ACM-W in 2012, Barr has been a driving force in more than tripling the number of ACM-W chapters around the world, from 50 to 180 today. One strategy that led to this growth was the introduction of special networking events in which colleges and universities with ACM-W chapters would invite students from neighboring colleges and encourage them to establish ACM-W chapters on their own campuses.   ACM-W Councils in Europe and India oversee activities in their respective regions.  Another notable area of growth during Barr’s tenure as Chair has been a significant increase in ACM-W Celebrations, small conferences in which women from specific geographic regions come together for career fairs, industry panels and technical presentations. Celebrations events have expanded to Cuba and the Philippines, and one event is tailored specifically for community college students. Last year, 25 ACM-W Celebrations took place around the world.

ACM-W members especially look forward to Connections, a monthly newsletter Barr instituted that is sent to 36,000 people each month and is considered a “must read.”

The Outstanding Contribution to ACM Award recognizes outstanding service contributions to the Association. Candidates are selected based on the value and degree of service overall, and may be given to up to three individuals each year.

Jeffrey Heer was honored for developing visualization languages that have changed the way people build and interact with charts and graphs across the Web. With the meteoric increase of data collection in recent years, tools are urgently needed to understand and see patterns within data. Jeffrey Heer, a Professor at the University of Washington, has been a leader in developing computer languages to create charts, graphs and other visualizations that help people explore and understand data. Heer’s earliest project, Prefuse, was developed in 2004 and became one of the first developer-friendly software packages for producing interactive visualizations. His later work with Mike Bostock on Protovis (2009) contributed a groundbreaking high-level language for Web-native data visualization. Heer then contributed to the development of Bostock’s subsequent D3.js (2011). D3.js quickly became the primary tool for creating interactive visualizations on the Web, and is used every day by thousands of Web developers worldwide. The Vega project, Heer's most recent contribution, builds on this earlier work to develop new representations that enable both human designers and automated algorithms to rapidly produce a wide range of interactive graphics. Data analytics firms and major media companies regularly publish visualizations created with these languages to engage millions of viewers. Importantly, Heer and his collaborators have made all of their visualization tools widely available as open source software.

The ACM Grace Murray Hopper Award is given to the outstanding young computer professional of the year, selected on the basis of a single recent major technical or service contribution. This award is accompanied by a prize of $35,000. The candidate must have been 35 years of age or less at the time the qualifying contribution was made. Financial support for this award is provided by Microsoft.

Amos Fiat and Moni Naor were honored for the development of broadcast encryption and traitor tracing systems. Sending broadcast transmissions that only paid subscribers have access to is one of the most important parts of a pay TV system. A traditional challenge of sending encrypted keys to subscribers has been that the pool of subscribers is constantly changing, as are the specific package of channels each customer may be subscribing to at any time. Traditional approaches to Broadcast Encryption would require TV providers to send either very long transmissions or for subscribers to store an inordinate number of cryptographic keys. In 1993, the Israeli team of Amos Fiat and Moni Naor published their landmark paper Broadcast Encryption, which proposed a system of broadcast encryption that was efficient, both in terms of the length of the transmissions the provider sends, and the number of keys a subscriber would need to store. Fiat and Naor’s work is widely regarded as laying the foundation of the broadcast encryption field. Their original ideas are now used by cable television and satellite radio providers to ensure that only paying subscribers can decrypt a broadcast. A form of broadcast encryption is also the standard key management system that is used to protect against the unauthorized copying of Blu-ray discs.

Building on this work, Fiat (Tel Aviv University) and Naor (Weizmann Institute of Science) collaborated with Benny Chor to invent traitor tracing. Traitor tracing enables legal parties who leak their keys to unauthorized parties to be tracked down and identified. Traitor tracing has been an important tool in the war against piracy.

The ACM Paris Kanellakis Theory and Practice Award honors specific theoretical accomplishments that have had a significant and demonstrable effect on the practice of computing. This award is accompanied by a prize of $10,000 and is endowed by contributions from the Kanellakis family, with additional financial support provided by ACM's Special Interest Groups on Algorithms and Computation Theory (SIGACT), Design Automation (SIGDA), Management of Data (SIGMOD), and Programming Languages (SIGPLAN), the ACM SIG Projects Fund, and individual contributions.

Jitendra Malik was honored for seminal contributions to computer vision that have led the field in image segmentation and object category recognition. It is estimated that 50% of brain power is devoted to visual processing. And as vision is the primary way in which we engage with the world, artificial intelligence (AI) systems which seek to mimic human cognition must incorporate computer vision. For example, it is important for an autonomous vehicle to distinguish between a large plastic bag on the roadway and the limb of a tree.

Malik is recognized as one of the world’s leading researchers in computer vision. He and his lab at UC Berkeley solved several important problems in computer vision, including how to remove “noise” from images in order to identify critical elements such as edges, how to segment images, and how to represent and match shapes. Many of Malik’s former graduate students are now recognized leaders in the field. Through his own research and mentorship, Malik has been a driving force in transforming computer vision from a niche interest to a successful and influential discipline. Computer vision plays an increasingly important role in social media, Internet search, entertainment and autonomous vehicle development.

The ACM - AAAI Allen Newell Award is presented to an individual selected for career contributions that have breadth within computer science, or that bridge computer science and other disciplines. The Newell award is accompanied by a prize of $10,000, provided by ACM and the Association for the Advancement of Artificial Intelligence (AAAI), and by individual contributions.

ACM will present the 2016 Software System Award, Grace Murray Hopper Award, Paris Kanellakis Theory and Practice Award, and Allen Newell Award at its annual Awards Banquet on June 24, 2017 in San Francisco, California.

Mahadev Satyanarayanan, Michael L. Kazar, Robert N. Sidebotham, David A. Nichols, Michael J. West, John H. Howard, Alfred Z. Spector and Sherri M. Nichols were honored for developing the Andrew File System (AFS). AFS was the first distributed file system designed for tens of thousands of machines, and pioneered the use of scalable, secure and ubiquitous access to shared file data. To achieve the goal of providing a common shared file system used by large networks of people, AFS introduced novel approaches to caching, security, management and administration. AFS is still in use today as both an open source system and as the file system in commercial applications. It has also inspired several cloud-based storage applications.

The 2016 Software System Award recipients designed and built the Andrew File System in the 1980s while working as a team at the Information Technology Center (ITC), a partnership between Carnegie Mellon University and IBM. Many other universities soon integrated AFS before it was introduced as a commercial application. Many of this year’s recipients also contributed to two foundational AFS papers: The ITC Distributed File System: Principles and Design, published in Proceedings of ACM SOSP 1985 and Scale and Performance in a Distributed File System, published in Proceedings of ACM SOSP 1987.

The ACM Software System Award is presented to an institution or individual(s) recognized for developing a software system that has had a lasting influence, reflected in contributions to concepts, in commercial acceptance, or both. The Software System Award carries a prize of $35,000. Financial support for the Software System Award is provided by IBM.

Thomas J. R. Hughes of the University of Texas at Austin was awarded the 2017 SIAM/ACM Prize in Computer Science and Engineering on March 2 at the SIAM Conference on CS&E (CSE17) in Atlanta, Georgia.

Hughes is Peter O'Donnell Jr. Chair in Computational and Applied Mathematics and Professor of Aerospace Engineering and Engineering Mechanics at the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin.

The prize honors Hughes for his pioneering work on finite element methods for PDEs. His work is used worldwide in engineering design and simulation, and has impacted every field of science that uses finite element methods, including medicine. He has also made pioneering contributions to the seamless integration of modeling methodologies with design representations. He has created entirely new fields of research, including Stabilized Methods, Variational Multiscale Methods, and Isogeometric Analysis, and continues to lead their development.

According to the citation: "The work of Thomas J. R. Hughes has had profound impact on computational science and engineering. His pioneering numerical methods for solving PDEs have been implemented in every contemporary commercial finite element code, and are used daily throughout the world in all areas of engineering design and simulation. Beyond engineering, his methods have impacted every field of science that uses finite element methods, including medicine. He has also made pioneering contributions to the seamless integration of modeling methodologies with design representations. He has created entirely new fields of research, including Stabilized Methods, Variational Multiscale Methods, and Isogeometric Analysis, and continues to lead their development."

For more information read the SIAM news release.