A
Adrian M. Caulfield
Researcher at Microsoft
Publications - 48
Citations - 6125
Adrian M. Caulfield is an academic researcher from Microsoft. The author has contributed to research in topics: Acceleration & Hardware acceleration. The author has an hindex of 20, co-authored 48 publications receiving 5388 citations. Previous affiliations of Adrian M. Caulfield include University of California, San Diego & University of California.
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Proceedings ArticleDOI
NV-Heaps: making persistent objects fast and safe with next-generation, non-volatile memories
Joel Coburn,Adrian M. Caulfield,Akel Ameen D,Laura M. Grupp,Rajesh Gupta,Ranjit Jhala,Steven Swanson +6 more
TL;DR: A lightweight, high-performance persistent object system called NV-heaps is implemented that provides transactional semantics while preventing these errors and providing a model for persistence that is easy to use and reason about.
Journal ArticleDOI
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,Stephen F. Heil,Amir Hormati,Joo-Young Kim,Sitaram Lanka,James R. Larus,Eric C. Peterson,Simon Pope,Aaron L. Smith,Jason Thong,Phillip Yi Xiao,Doug Burger +22 more
TL;DR: The authors deployed the reconfigurable fabric in a bed of 1,632 servers and FPGAs in a production datacenter and successfully used it to accelerate the ranking portion of the Bing Web search engine by nearly a factor of two.
Journal ArticleDOI
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,Stephen F. Heil,Amir Hormati,Joo-Young Kim,Sitaram Lanka,James R. Larus,Eric C. Peterson,Simon Pope,Aaron L. Smith,Jason Thong,Phillip Yi Xiao,Doug Burger +22 more
TL;DR: The requirements and architecture of the fabric are described, the critical engineering challenges and solutions needed to make the system robust in the presence of failures are detailed, and the performance, power, and resilience of the system when ranking candidate documents are measured.
Proceedings ArticleDOI
A cloud-scale acceleration architecture
Adrian M. Caulfield,Eric S. Chung,Andrew Putnam,Hari Angepat,Jeremy Fowers,Michael Haselman,Stephen F. Heil,Matt Humphrey,Puneet Kaur,Joo-Young Kim,Lo Daniel,Todd Massengill,Kalin Ovtcharov,Michael K. Papamichael,Lisa Woods,Sitaram Lanka,Derek Chiou,Doug Burger +17 more
TL;DR: A new cloud architecture that uses reconfigurable logic to accelerate both network plane functions and applications, and is much more scalable than prior work which used secondary rack-scale networks for inter-FPGA communication.
Proceedings ArticleDOI
A configurable cloud-scale DNN processor for real-time AI
Jeremy Fowers,Kalin Ovtcharov,Michael K. Papamichael,Todd Massengill,Ming Liu,Lo Daniel,Shlomi Alkalay,Michael Haselman,Logan Adams,Mahdi Ghandi,Stephen F. Heil,Prerak Patel,Adam Sapek,Gabriel Weisz,Lisa Woods,Sitaram Lanka,Steven K. Reinhardt,Adrian M. Caulfield,Eric S. Chung,Doug Burger +19 more
TL;DR: This paper describes the NPU architecture for Project Brainwave, a production-scale system for real-time AI, and achieves more than an order of magnitude improvement in latency and throughput over state-of-the-art GPUs on large RNNs at a batch size of 1.5 teraflops.