"Simba," by Yakun Sophia Shao, et al., presents a scalable deep learning accelerator architecture that tackles issues ranging from chip integration technology to...Natalie Enright Jerger From Communications of the ACM | June 2021
This work investigates and quantifies the costs and benefits of using multi-chip-modules with fine-grained chiplets for deep learning inference, an application...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 From Communications of the ACM | June 2021
"Scalable Signal Reconstruction for a Broad Range of Applications," by Abolfazl Asudeh, et al. shows that algorithmic insights about SRP, combined with database...Zachary G. Ives From Communications of the ACM | February 2021
Most of the common approaches for solving signal reconstruction problem do not scale to large problem sizes. We propose a novel and scalable algorithm for solving...Abolfazl Asudeh, Jees Augustine, Saravanan Thirumuruganathan, Azade Nazi, Nan Zhang, Gautam Das, Divesh Srivastava From Communications of the ACM | February 2021
"SkyCore," by Mehrdad Moradi, et al., addresses an exciting use case for Unmanned Aerial Vehicles in which UAVs can act as mobile base stations for the cellular...Richard Han From Communications of the ACM | January 2021
We argue for and propose an alternate, radical edge evolved packet core design, called SkyCore, that pushes the EPC functionality to the extreme edge of the core...Mehrdad Moradi, Karthikeyan Sundaresan, Eugene Chai, Sampath Rangarajan, Z. Morley Mao From Communications of the ACM | January 2021
In "Constant Overhead Quantum Fault Tolerance with Quantum Expander Codes," by Omar Fawzi, et al., the authors produce an algorithm that can rapidly deduce the...Daniel Gottesman From Communications of the ACM | January 2021
In this paper, we study the asymptotic scaling of the space overhead needed for fault-tolerant quantum computation.
Omar Fawzi, Antoine Grospellier, Anthony Leverrier From Communications of the ACM | January 2021
The system described in "SATURN: An Introduction to the Internet of Materials" works passively, energized essentially by static electricity generated as layers...Joseph A. Paradiso From Communications of the ACM | December 2020
We propose an Internet of Materials, where the very materials of objects and surfaces are augmented or manufactured to have computational capabilities.
Nivedita Arora, Thad Starner, Gregory D. Abowd From Communications of the ACM | December 2020
How to produce a convolutional neural net that is small enough to run on a mobile device, and accurate enough to be worth using? The strategies in "Enabling AI...David Alexander Forsyth From Communications of the ACM | December 2020
We present a novel approach to running state-of-the-art AI algorithms in edge devices, and propose two efficient approximations to standard convolutional neural...Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, Ali Farhadi From Communications of the ACM | December 2020
Can we build purpose-built, warehouse-scale datacenters customized for large-scale arrays of ASIC accelerators or, to use a term coined in the paper by Michael...Parthasarathy Ranganathan From Communications of the ACM | July 2020
This paper distills lessons from Bitcoin ASIC Clouds and applies them to other large scale workloads, showing superior TCO (total cost of ownership) versus CPU...Michael Bedford Taylor, Luis Vega, Moein Khazraee, Ikuo Magaki, Scott Davidson, Dustin Richmond From Communications of the ACM | July 2020
Instead of handing trace records off to a collector for long-term storage and future processing, the system described in "Pivot Tracing: Dynamic Causal Monitoring...Rebecca Isaacs From Communications of the ACM | March 2020
This paper presents Pivot Tracing, a monitoring framework for distributed systems, which addresses the limitations of today's monitoring and diagnosis tools by...Jonathan Mace, Ryan Roelke, Rodrigo Fonseca From Communications of the ACM | March 2020
OpenPiton research is one of the watershed moments in the fundamental shift toward the construction of an open source ecosystem for implementing prototype chips...Michael B. Taylor From Communications of the ACM | December 2019
We present OpenPiton, an open source framework for building scalable architecture research prototypes from one core to 500 million cores.
Jonathan Balkind, Michael McKeown, Yaosheng Fu, Tri Nguyen, Yanqi Zhou, Alexey Lavrov, Mohammad Shahrad, Adi Fuchs, Samuel Payne, Xiaohua Liang, Matthew Matl, David Wentzlaff From Communications of the ACM | December 2019
DeepXplore brings a software testing perspective to deep neural networks and, in doing so, creates the opportunity for enormous amounts of follow-on work in several...David G. Andersen From Communications of the ACM | November 2019
We design, implement, and evaluate DeepXplore, the first white-box framework for systematically testing real-world deep learning systems.
Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana From Communications of the ACM | November 2019