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Research Labs
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3D Deep Learning
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Artificial Intelligence and Machine Learning
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2021
Softermax: Hardware/Software Co-Design of an Efficient Softmax for Transformers
Jacob R. Stevens,
Rangharajan Venkatesan
,
Steve Dai
,
Brucek Khailany
, Anand Raghunathan
Optimizing Selective Protection for CNN Resilience
Abdulrahman Mahmoud,
Siva Hari
, Christopher W. Fletcher, Sarita V. Adve,
Charbel Sakr
, Naresh Shanbhag,
Pavlo Molchanov
,
Michael B. Sullivan
, Timothy Tsai,
Steve Keckler
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators
Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi,
Angshuman Parashar
,
Po-An Tsai
, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna
Simba: scaling deep-learning inference with chiplet-based architecture
Yakun Sophia Shao,
Jason Clemons
,
Rangharajan Venkatesan
,
Brian Zimmer
,
Matt Fojtik
,
Ted Jiang
,
Ben Keller
, Alicia Klinefelter,
Nathaniel Pinckney
, Priyanka Raina,
Stephen Tell
,
Yanqing Zhang
,
William Dally
,
Joel Emer
,
Tom Gray
,
Brucek Khailany
,
Steve Keckler
ACM Research Highlight
GAMMA: Exploiting Gustavson’s Algorithm to Accelerate Sparse Matrix Multiplication
Guowei Zhang, Nithya Attaluri,
Joel Emer
, Daniel Sanchez
VS-QUANT: Per-Vector Scaled Quantization for Accurate Low-Precision Neural Network Inference
Steve Dai
,
Rangharajan Venkatesan
,
Haoxing (Mark) Ren
,
Brian Zimmer
,
William Dally
,
Brucek Khailany
Learning Sparse Matrix Row Permutations for Efficient SpMM on GPU Architectures
Atefeh Mehrabi,
Donghyuk Lee
,
Niladrish Chatterjee
, Danial J. Sorin, Benjamin C. Lee,
Mike O'Connor
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Hari
,
Michael B. Sullivan
, Timothy Tsai,
Steve Keckler
Heterogeneous Dataflow Accelerators for Multi-DNN Workloads
Hyoukjun Kwon, Liangzhen Lai,
Michael Pellauer
, Tushar Krishna, Yu-Hsin Chen, Vikas Chandra
Flexion: A Quantitative Metric for Flexibility in DNN Accelerators
Hyoukjun Kwon,
Michael Pellauer
,
Angshuman Parashar
, Tushar Krishna
