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Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Naoya Maruyama, Tatsuo Nomura, Kento Sato, Satoshi Matsuoka

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Tags: Computer science, CUDA, MPI, nVidia, Optimization, Package, Performance, Programming Languages, Programming techniques, Tesla M2050

October 15, 2011 by hgpu

Operating Systems Challenges for GPU Resource Management

Shinpei Kato, Scott Brandt, Yutaka Ishikawa, Ragunathan (Raj) Rajkumar

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Tags: Computer science, CUDA, GPU cluster, nVidia, OpenCL, Operating systems, Virtualization

October 15, 2011 by hgpu

Towards Utilizing Remote GPUs for CUDA Program Execution

Xiaonan Ji, Spencer Davis, Erikson Hardesty, Xu Liang, Sabuj Saha, Hai Jiang

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Networks, nVidia

October 15, 2011 by hgpu

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Shuai Che, Jeremy W. Sheaffer, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, Performance

October 15, 2011 by hgpu

Effects of compression on data intensive algorithms

Ahmed Adnan Aqrawi

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Tags: Algorithms, Compression, Computer science, CUDA, Filtering, Image processing, nVidia, Seismology, Tesla C1060, Tesla C2050, Thesis

October 15, 2011 by hgpu

Bandwidth Reduction Through Multithreaded Compression of Seismic Images

Ahmed A. Aqrawi, Anne C. Elster

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Tags: Algorithms, Compression, Computer science, CUDA, Image processing, nVidia, Seismology, Tesla C2050

October 15, 2011 by hgpu

Speeding up the MATLAB complex networks package using graphic processors

Zhang Bai-Da, Tang Yu-Hua, Wu Jun-Jie, Li Xin

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Tags: Algorithms, Computer science, CUDA, Networks, nVidia, nVidia GeForce GTX 480

October 15, 2011 by hgpu

GPU fluids in production: a compiler approach to parallelism

Dan Bailey, Ian Masters, Matt Warner

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Tags: Code generation, Compilers, Computer science, Image processing, nVidia, Performance, Presentation, PTX, Tesla C2050

October 15, 2011 by hgpu

Accelerating code on multi-cores with FastFlow

Marco Aldinucci, Marco Danelutto, Peter Kilpatrick, Massimiliano Meneghin, Massimo Torquati

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Tags: Computer science, Memory, Package, Performance, Programming techniques

October 15, 2011 by hgpu

An Analysis of Programmer Productivity versus Performance for High Level Data Parallel Programming

Alex Cole, Alistair McEwan, Satnam Singh

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Tags: Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 460, Programming techniques

October 14, 2011 by hgpu

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

Michael Bauer, Henry Cook, Brucek Khailany

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Tags: Benchmarking, Computer science, CUDA, Memory model, nVidia, Optimization, Package, Performance, Tesla C2050

October 14, 2011 by hgpu

OptiML: An implicitly parallel domain-specific language for machine learning

Arvind K. Sujeeth, HyoukJoong Lee, Kevin J. Brown, Tiark Rompf, Hassan Chafi, Michael Wu, Anand R. Atreya, Martin Odersky, Kunle Olukotun

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Tags: Computer science, Heterogeneous systems, Machine learning, nVidia, OpenCL, Optimization, Tesla C2050

October 14, 2011 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

See all packages

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high performance computing on graphics processing units: hgpu.org

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Operating Systems Challenges for GPU Resource Management

Towards Utilizing Remote GPUs for CUDA Program Execution

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Effects of compression on data intensive algorithms

Bandwidth Reduction Through Multithreaded Compression of Seismic Images

Speeding up the MATLAB complex networks package using graphic processors

GPU fluids in production: a compiler approach to parallelism

Accelerating code on multi-cores with FastFlow

An Analysis of Programmer Productivity versus Performance for High Level Data Parallel Programming

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

OptiML: An implicitly parallel domain-specific language for machine learning

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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