Publications

Our publications provide insight into some of our leading-edge research.

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2016

Tensor Contractions with Extended BLAS Kernels on CPU and GPU
Yang Shi, U. N. Niranjan, Animashree Anandkumar, Cris Cecka
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design.
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, Steve Keckler
Approxilyzer: Towards A Systematic Framework for Instruction-Level Approximate Computing and its Application to Hardware Resiliency
Radha Venkatagiri, Abdulrahman Mahmoud, Siva Hari, Sarita Adve
All-Inclusive ECC: Thorough End-to-End Protection for Reliable Computer Memory
Jungrae Kim, Michael B. Sullivan, Sangkug Lym, Mattan Erez
S-Step and Communication-Avoiding Iterative Methods
Maxim Naumov
Selective GPU Caches to Eliminate CPU-GPU HW Cache Coherence
Neha Agarwal, David Nellans, Eiman Ebrahimi, Thomas F. Wenisch, John Danskin, Steve Keckler
Towards High Performance Paged Memory for GPUs
Tianhao Zheng, David Nellans, Arslan Zulfiqar, Mark Stephenson, Steve Keckler
A Case for Toggle-Aware Compression for GPU Systems
Gennady Pekhimenko, Evgeny Bolotin, Nandita Vijaykumar, Onur Mutlu, Todd C. Mowry, Steve Keckler
Parallel Spectral Graph Partitioning
Maxim Naumov, Timothy Moon

2011

Allocation-oriented Algorithm Design with Application to GPU Computing, Ph.D. Dissertation
Duane Merrill
Thrust: A Productivity-Oriented Library for CUDA
Nathan Bell, Jared Hoberock
High Performance and Scalable GPU Graph Traversal
Duane Merrill, Michael Garland, Andrew Grimshaw
Parallel Solution of Sparse Triangular Linear Systems in the Preconditioned Iterative Methods on the GPU
Maxim Naumov