high performance computing on graphics processing units: hgpu.org

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Functional High Performance Financial IT

Jost Berthold, Andrzej Filinski, Fritz Henglein, Ken Friis Larsen, Mogens Steffensen, Brian Vinter

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Tags: Finance, OpenCL

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

Efficient Mapping of Streaming Applications for Image Processing on Graphics Cards

Richard Membarth, Hritam Dutta, Frank Hannig, Jurgen Teich

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Tags: Algorithms, CUDA, Image processing, nVidia, Package, Tesla C1060

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

Accelerating Large Scale Image Analyses on Parallel CPU-GPU Equipped Systems

George Teodoro, Tahsin M. Kurc, Tony Pan, Lee Cooper, Jun Kong, Patrick Widener, Joel H. Saltz

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Tags: CUDA, Heterogeneous systems, Image processing, nVidia, Tesla M2070

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

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

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

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high performance computing on graphics processing units: hgpu.org

Applications

Functional High Performance Financial IT

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

Efficient Mapping of Streaming Applications for Image Processing on Graphics Cards

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

Accelerating Large Scale Image Analyses on Parallel CPU-GPU Equipped Systems

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

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

Recent source codes

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

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

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