Time for Two Annual Turing Awards

ACM should bestow two Turing Awards each year, starting immediately.

Andrew A. Chien

It Came From Outer Space!

The resilience of the Internet with alternative paths, including satellite and undersea and land cable as well as high speed laser links, might play a critical part of overcoming the side effects of a major CME (coronal mass …

Vinton G. Cerf

The Search for Unlimited Productivity

Doug Meil considers the continuing search for the next great software development methodology.

Doug Meil

Getting Down to Basics

2020 ACM A.M. Turing Award recipients Alfred Aho and Jeffrey Ullman helped develop formal language theory, invented efficient algorithms to drive the tasks of a compiler, and put them all together in 'The Dragon Book.'

Neil Savage

Deceiving AI

The uncanny power of machine learning can be turned against it.

Don Monroe

Jack Minker (1927–2021)

ACM Fellow Jack Minker was a leader in the development of automating logistic reasoning, but he is perhaps best known for his efforts to promote the social responsibility of scientists and human rights.

Simson Garfinkel, Eugene H. Spafford

Taking the Heat

Maxwell's demon and the high cost of erasure.

Marina Krakovsky

Let the Algorithm Decide?

Algorithms fail their first test to replace student exams.

Chris Edwards

The Risks of Election Believability (or Lack Thereof)

With 90% of the 2020 U.S. general election ballot contents verifiable by paper, why do only 65% of voters trust the results?

Rebecca T. Mercuri, Peter G. Neumann

Aversion to Versions

Code needs to run anywhere as long as the necessary dependencies can be resolved.

George V. Neville-Neil

Locality and Professional Life

The locality principle extends beyond computer memories. It teaches us something about being human.

Peter J. Denning

A Vision to Compute like Nature: Thermodynamically

Advocating a new, physically grounded, computational paradigm centered on thermodynamics and an emerging understanding of using thermodynamics to solve problems.

Todd Hylton, Thomas M. Conte, Mark D. Hill

Depth and Persistence: What Researchers Need to Know About Impostor Syndrome

Understanding impostor syndrome's complexity and its effect on research persistence.

Danfeng (Daphne) Yao

Collusion Rings Threaten the Integrity of Computer Science Research

Experiences discovering attempts to subvert the peer-review process.

Michael L. Littman

The SPACE of Developer Productivity

There's more to it than you think.

Nicole Forsgren, Margaret-Anne Storey, Chandra Maddila, Thomas Zimmermann, Brian Houck, Jenna Butler

Toward Confidential Cloud Computing

Extending hardware-enforced cryptographic protection to data while in use.

Mark Russinovich, Manuel Costa, Cédric Fournet, David Chisnall, Antoine Delignat-Lavaud, Sylvan Clebsch, Kapil Vaswani, Vikas Bhatia

CoCoPIE: Enabling Real-Time AI on Off-the-Shelf Mobile Devices via Compression-Compilation Co-Design

A new framework allows intelligence on mainstream end devices without special hardware.

Hui Guan, Shaoshan Liu, Xiaolong Ma, Wei Niu, Bin Ren, Xipeng Shen, Yanzhi Wang, Pu Zhao

On the Requirements Engineer Role

The requirements engineer role is defined differently within most organizations.

Xavier Franch, Cristina Palomares, Tony Gorschek

Dynamics of Gender Bias in Computing

A new dataset significantly revises both scholarly assessment and popular understanding about gender bias in computing.

Thomas J. Misa

Securing Internet Applications from Routing Attacks

Application-layer and network-layer defenses are critical for fortifying routing attacks.

Yixin Sun, Maria Apostolaki, Henry Birge-Lee, Laurent Vanbever, Jennifer Rexford, Mung Chiang, Prateek Mittal

Technical Perspective: Race Logic Presents a Novel Form of Encoding

"In-Sensor Classification With Boosted Race Trees," by Georgios Tzimpragos, et al., proposes a surprising, novel, and creative approach to post-Moore's Law computing by rethinking the digital/analog boundary.

Abhishek Bhattacharjee

In-Sensor Classification With Boosted Race Trees

We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal.

Georgios Tzimpragos, Advait Madhavan, Dilip Vasudevan, Dmitri Strukov, Timothy Sherwood

Technical Perspective: A Chiplet Prototype System for Deep Learning Inference

"Simba," by Yakun Sophia Shao, et al., presents a scalable deep learning accelerator architecture that tackles issues ranging from chip integration technology to workload partitioning and non-uniform latency effects on deep neural …

Natalie Enright Jerger

Simba: Scaling Deep-Learning Inference with Chiplet-Based Architecture

This work investigates and quantifies the costs and benefits of using multi-chip-modules with fine-grained chiplets for deep learning inference, an application domain with large compute and on-chip storage requirements.

Yakun Sophia Shao, Jason Cemons, Rangharajan Venkatesan, Brian Zimmer, Matthew Fojtik, Nan Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen G. Tell, Yanqing Zhang, William J. Dally, Joel Emer, C. Thomas Gray, Brucek Khailany, Stephen W. Keckler

Shaping the Foundations of Programming Languages

ACM A.M. Turing Award recipients Alfred Aho and Jeffrey Ullman discuss their early work, the 'Dragon Book,' and the future of 'live' computer science education.

Leah Hoffmann