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Programming Languages, Systems and Tools

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Programming Languages, Systems and Tools

2023

Legate Sparse: Distributed Sparse Computing in Python

Rohan Yadav, Wonchan Lee, Melih Elibol, Taylor Patti, Manolis Papadakis, Michael Garland, Alex Aiken, Fredrik Kjolstad, Michael Bauer

cuCatch: A Debugging Tool for Efficiently Catching Memory Safety Violations in CUDA Applications

Mohamed Tarek Ibn Ziad, Sana Damani, Aamer Jaleel, Stephen W. Keckler, Mark Stephenson

PLDI

Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence

Michael Bauer, Elliott Slaughter, Sean Treichler, Wonchan Lee, Michael Garland, Alex Aiken

Parsimony: Enabling SIMD/Vector Programming in Standard Compiler Flows

Vijay Kandiah, Daniel Lustig, Oreste Villa, David Nellans, Nikos Hardavellas

2022

Demystifying Map Space Exploration for NPUs

Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna

Slang Shading Language Advances

Yong He, Petrik Clarberg, Theresa Foley

Research Advances Toward Real-Time Path Tracing

Petrik Clarberg, Simon Kallweit, Craig Kolb, Pawel Kozlowski, Yong He, Lifan Wu, Edward Liu

Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators

Prasanth Chatarasi, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Tushar Krishna, Vivek Sarkar

2021

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

Cooperative Profile Guided Optimization

Mark Stephenson, Ram Rangan, Steve Keckler

Efficient Multi-GPU Shared Memory via Automatic Optimization of Fine-Grained Transfers

Harini Muthukrishnan, David Nellans, Daniel Lustig, Jeffrey Fessler, Thomas Wenisch

PGZ: Automatic Zero-Value Code Specialization

Mark Stephenson, Ram Rangan

Scaling Implicit Parallelism via Dynamic Control Replication

Michael Bauer, Wonchan Lee, Elliott Slaughter, Zhihao Jia, Mario Di Renzo, Manolis Papadakis, Galen Shipman, Patrick McCormick, Michael Garland, Alex Aiken

Hardware Abstractions for Targeting EDDO Architectures with the Polyhedral Model

Angshuman Parashar, Prasanth Chatarasi, Po-An Tsai

2020

Locality-Centric Data and Threadblock Management for Massive GPUs

Mahmoud Khairy, Vadim Nikiforov, David Nellans, Timothy G. Rogers

A Programmable Approach to Neural Network Compression

Vinu Joseph, Ganesh L. Gopalakrishnan, Saurav Muralidharan, Michael Garland, Animesh Garg

Zeroploit: Exploiting Zero Valued Operands in Interactive Gaming Applications

Ram Rangan, Mark Stephenson, Aditya Ukarande, Shyam Murthy, Virat Agarwal, Marc Blackstein

There’s Plenty of Room at the Top: What Will Drive Computer Performance after Moore’s Law?

Charles E. Leiserson, Neil C. Thompson, Joel Emer, Bradley C. Kuszmaul, Butler W. Lampson, Daniel Sanchez , Tao B. Schardl

Speculative Reconvergence for Improved SIMT Efficiency

Sana Damani, Daniel Johnson, Mark Stephenson, Eddie Yan, Olivier Giroux, Michael McKeown, Steve Keckler

2019

Legate NumPy: Accelerated and Distributed Array Computing

Michael Bauer, Michael Garland

NVBit: A Dynamic Binary Instrumentation Framework for NVIDIA GPUs

Oreste Villa, Mark Stephenson, David Nellans, Steve Keckler

Task Bench: A Parameterized Benchmark for Evaluating Parallel Runtime Performance

Elliott Slaughter, Wei Wu, Yuankun Fu, Legend Brandenburg, Nicolai Garcia, Wilhem Kautz, Emily Marx, Kaleb S. Morris, Qinglei Cao, George Bosilca, Seema Mirchandaney, Wonchan Lee, Sean Treichler, Patrick McCormick, Alex Aiken

Timeloop: A Systematic Approach to DNN Accelerator Evaluation

Angshuman Parashar, Priyanka Raina, Yakun Sophia Shao, Yu-Hsin Chen, Victor A. Ying, Anurag Mukkara, Rangharajan Venkatesan, Brucek Khailany, Steve Keckler, Joel Emer

Throughput-oriented GPU memory allocation

Isaac Gelado, Michael Garland