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2023

Efficient Transformer Inference with Statically Structured Sparse Attention

Steve Dai, Hasan Genc, Rangharajan Venkatesan, Brucek Khailany

A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm

Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, Charbel Sakr, William Dally, Tom Gray, Brucek Khailany

2022

LNS-Madam: Low-Precision Training in Logarithmic Number System Using Multiplicative Weight Update

Jiawei Zhao, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, Mustafa Ali, Ming-Yu Liu, Brucek Khailany, William Dally, Anima Anandkumar

Saving PAM4 Bus Energy with SMOREs: Sparse Multi-level Opportunistic Restricted Encodings

Mike O'Connor, Donghyuk Lee, Niladrish Chatterjee, Michael B. Sullivan, Steve Keckler

2021

Softermax: Hardware/Software Co-Design of an Efficient Softmax for Transformers

Jacob R. Stevens, Rangharajan Venkatesan, Steve Dai, Brucek Khailany, Anand Raghunathan

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

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

2019

MAGNet: A Modular Accelerator Generator for Neural Networks

Rangharajan Venkatesan, Sophia Shao, Miaorong Wang, Jason Clemons, Steve Dai, Matt Fojtik, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Yanqing Zhang, Brian Zimmer, William Dally, Joel Emer, Steve Keckler, Brucek Khailany

Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture

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

Best Paper award
IEEE Micro Top Picks in Computer Architecture (Honorable Mention)

A 0.11 pJ/Op, 0.32-128 TOPS, Scalable Multi-Chip-Module-based Deep Neural Network Accelerator Designed with a High-Productivity VLSI Methodology

Rangharajan Venkatesan, Sophia Shao, Brian Zimmer, Jason Clemons, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Steve Keckler, Brucek Khailany

2018

A Modular Digital VLSI Flow for High-Productivity SoC Design

Brucek Khailany, Evgeni Krimer, Rangharajan Venkatesan, Jason Clemons, Joel Emer, Matt Fojtik, Alicia Klinefelter, Michael Pellauer, Nathaniel Pinckney, Sophia Shao, Shreesha Srinath, Christopher Torng, Sam (Likun) Xi, Yanqing Zhang, Brian Zimmer

2017

Xylem: Enhancing Vertical Thermal Conduction in 3D Processor-Memory Stacks

Aditya Agrawal, Josep Torrellas, Sachin Idgunji

Ambit: In-Memory Accelerator for Bulk Bitwise Operations Using Commodity DRAM Technology

Vivek Seshadri, Donghyuk Lee, Thomas Mullins, Hasan Hassan, Amirali Boroumand, Jeremie Kim, Michael A. Kozuch, Onur Mutlu, Phillip B. Gibbons, Todd C. Mowry

Detecting and Mitigating Data-Dependent DRAM Failures by Exploiting Current Memory Content

Samira Khan, Chris Wilkerson, Zhe Wang, Alaa R. Alameldeen, Donghyuk Lee, Onur Mutlu

2016

Snatch: Opportunistically Reassigning Power Allocation between Processor and Memory in 3D Stacks

Dimitrios Skarlatos, Renji Thomas, Aditya Agrawal, Shibin Qin, Robert Pilawa-Podgurski, Ulya R. Karpuzcu, Radu Teodorescu, Nam Sung Kim, Josep Torrellas

2013

21st Century Digital Design Tools

William Dally, Chris Malachosky, Steve Keckler