Development and evaluation of emerging design patterns for ubiquitous computing. - Eric S. Chung; Jason I. Hong; James Lin; Madhu K. Prabaker; James A. Landay; Alan L. Liu (Conference on Designing Interactive Systems, 2004)

TRUSS: A Reliable, Scalable Server Architecture. - Brian T. Gold; Jangwoo Kim; Jared C. Smolens; Eric S. Chung; Vasileios Liaskovitis; Eriko Nurvitadhi; Babak Falsafi; James C. Hoe; Andreas Nowatzyk (IEEE Micro, 2005)

PROToFLEX: FPGA-accelerated Hybrid Functional Simulator. - Eric S. Chung; Eriko Nurvitadhi; James C. Hoe; Babak Falsafi; Ken Mai (IPDPS, 2007)

A complexity-effective architecture for accelerating full-system multiprocessor simulations using FPGAs. - Eric S. Chung; Eriko Nurvitadhi; James C. Hoe; Babak Falsafi; Ken Mai (FPGA, 2008)

Implementing a high-performance multithreaded microprocessor: A case study in high-level design and validation. - Eric S. Chung; James C. Hoe (MEMOCODE, 2009)

ProtoFlex: Towards Scalable, Full-System Multiprocessor Simulations Using FPGAs. - Eric S. Chung; Michael Papamichael; Eriko Nurvitadhi; James C. Hoe; Ken Mai; Babak Falsafi (ACM Trans. Reconfigurable Technol. Syst., 2009)

Single-Chip Heterogeneous Computing: Does the Future Include Custom Logic, FPGAs, and GPGPUs? - Eric S. Chung; Peter A. Milder; James C. Hoe; Ken Mai (MICRO, 2010)

High-Level Design and Validation of the BlueSPARC Multithreaded Processor. - Eric S. Chung; James C. Hoe (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2010)

CoRAM: an in-fabric memory architecture for FPGA-based computing. - Eric S. Chung; James C. Hoe; Ken Mai (FPGA, 2011)

Towards a Universal FPGA Matrix-Vector Multiplication Architecture. - Srinidhi Kestur; John D. Davis; Eric S. Chung (FCCM, 2012)

Prototype and evaluation of the CoRAM memory architecture for FPGA-based computing. - Eric S. Chung; Michael Papamichael; Gabriel Weisz; James C. Hoe; Ken Mai (FPGA, 2012)

Reconfigurable computing in the era of post-silicon scaling [panel discussion]. - Eric S. Chung; Doug Burger; Mike Butts; Jan Gray; Chuck Thacker; Kees A. Vissers; John Wawrzynek (FCCM, 2013)

ShrinkWrap: Compiler-Enabled Optimization and Customization of Soft Memory Interconnects. - Eric S. Chung; Michael Papamichael (FCCM, 2013)

Towards automatic customization of interconnect and memory in the CoRAM abstraction (abstract only). - Eric S. Chung; Michael Papamichael (FPGA, 2013)

Cross-platform FPGA accelerator development using CoRAM and CONNECT. - Eric S. Chung; Michael Papamichael; Gabriel Weisz; James C. Hoe (FPGA, 2013)

LINQits: big data on little clients. - Eric S. Chung; John D. Davis; Jaewon Lee (ISCA, 2013)

A High Memory Bandwidth FPGA Accelerator for Sparse Matrix-Vector Multiplication. - Jeremy Fowers; Kalin Ovtcharov; Karin Strauss; Eric S. Chung; Greg Stitt (FCCM, 2014)

FPGA-Accelerated Simulation of Computer Systems - Hari Angepat; Derek Chiou; Eric S. Chung; James C. Hoe (Morgan & Claypool Publishers, 2014)

Toward accelerating deep learning at scale using specialized hardware in the datacenter. - Kalin Ovtcharov; Olatunji Ruwase; Joo-Young Kim 001; Jeremy Fowers; Karin Strauss; Eric S. Chung (Hot Chips Symposium, 2015)

Agile Co-Design for a Reconfigurable Datacenter. - Shlomi Alkalay; Hari Angepat; Adrian M. Caulfield; Eric S. Chung; Oren Firestein; Michael Haselman; Stephen Heil; Kyle Holohan; Matt Humphrey; Tamás Juhász; Puneet Kaur; Sitaram Lanka; et al. (FPGA, 2016)

A cloud-scale acceleration architecture. - Adrian M. Caulfield; Eric S. Chung; Andrew Putnam; Hari Angepat; Jeremy Fowers; Michael Haselman; Stephen Heil; Matt Humphrey; Puneet Kaur; Joo-Young Kim 001; Daniel Lo; Todd Massengill; et al. (MICRO, 2016)

A reconfigurable fabric for accelerating large-scale datacenter services. - Andrew Putnam; Adrian M. Caulfield; Eric S. Chung; Derek Chiou; Kypros Constantinides; John Demme; Hadi Esmaeilzadeh; Jeremy Fowers; Gopi Prashanth Gopal; Jan Gray; Michael Haselman; Scott Hauck; et al. (Commun. ACM, 2016)

Deep Learning in the Enhanced Cloud. - Eric S. Chung (ISPD, 2017)

Configurable Clouds. - Adrian M. Caulfield; Eric S. Chung; Andrew Putnam; Hari Angepat; Daniel Firestone; Jeremy Fowers; Michael Haselman; Stephen Heil; Matt Humphrey; Puneet Kaur; Joo-Young Kim 001; Daniel Lo; et al. (IEEE Micro, 2017)

A Configurable Cloud-Scale DNN Processor for Real-Time AI. - Jeremy Fowers; Kalin Ovtcharov; Michael Papamichael; Todd Massengill; Ming Liu; Daniel Lo; Shlomi Alkalay; Michael Haselman; Logan Adams; Mahdi Ghandi; Stephen Heil; Prerak Patel; et al. (ISCA, 2018)

Azure Accelerated Networking: SmartNICs in the Public Cloud. - Daniel Firestone; Andrew Putnam; Sambrama Mundkur; Derek Chiou; Alireza Dabagh; Mike Andrewartha; Hari Angepat; Vivek Bhanu; Adrian M. Caulfield; Eric S. Chung; Harish Kumar Chandrappa; Somesh Chaturmohta; et al. (NSDI, 2018)

Serving DNNs in Real Time at Datacenter Scale with Project Brainwave. - Eric S. Chung; Jeremy Fowers; Kalin Ovtcharov; Michael Papamichael; Adrian M. Caulfield; Todd Massengill; Ming Liu; Daniel Lo; Shlomi Alkalay; Michael Haselman; Maleen Abeydeera; Logan Adams; et al. (IEEE Micro, 2018)

SysML: The New Frontier of Machine Learning Systems. - Alexander Ratner; Dan Alistarh; Gustavo Alonso; David G. Andersen; Peter Bailis; Sarah Bird; Nicholas Carlini; Bryan Catanzaro; Eric S. Chung; Bill Dally; Jeff Dean; Inderjit S. Dhillon; et al. (CoRR, 2019)

Inside Project Brainwave's Cloud-Scale, Real-Time AI Processor. - Jeremy Fowers; Kalin Ovtcharov; Michael K. Papamichael; Todd Massengill; Ming Liu; Daniel Lo; Shlomi Alkalay; Michael Haselman; Logan Adams; Mahdi Ghandi; Stephen Heil; Prerak Patel; et al. (IEEE Micro, 2019)

Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point. - Bita Darvish Rouhani; Daniel Lo; Ritchie Zhao; Ming Liu; Jeremy Fowers; Kalin Ovtcharov; Anna Vinogradsky; Sarah Massengill; Lita Yang; Ray Bittner; Alessandro Forin; Haishan Zhu; et al. (NeurIPS, 2020)

With Shared Microexponents, A Little Shifting Goes a Long Way. - Bita Darvish Rouhani; Ritchie Zhao; Venmugil Elango; Rasoul Shafipour; Mathew Hall; Maral Mesmakhosroshahi; Ankit More; Levi Melnick; Maximilian Golub; Girish Varatkar; Lai Shao; Gaurav Kolhe; et al. (ISCA, 2023)

Shared Microexponents: A Little Shifting Goes a Long Way. - Bita Rouhani; Ritchie Zhao; Venmugil Elango; Rasoul Shafipour; Mathew Hall; Maral Mesmakhosroshahi; Ankit More; Levi Melnick; Maximilian Golub; Girish Varatkar; Lei Shao; Gaurav Kolhe; et al. (CoRR, 2023)

Microscaling Data Formats for Deep Learning. - Bita Darvish Rouhani; Ritchie Zhao; Ankit More; Mathew Hall; Alireza Khodamoradi; Summer Deng; Dhruv Choudhary; Marius Cornea; Eric Dellinger; Kristof Denolf; Dusan Stosic; Venmugil Elango; et al. (CoRR, 2023)