high performance computing on graphics processing units: hgpu.org

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OpenCL Parallel Programming Development Cookbook

Raymond Tay

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Tags: Book, Computer science, Heterogeneous systems, OpenCL, Tutorial

September 27, 2013 by hgpu

GPU-TLS: An Efficient Runtime for Speculative Loop Parallelization on GPUs

Chenggang Zhang, Guodong Han, Cho-Li Wang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Performance, Tesla M2050

September 27, 2013 by hgpu

Java with Auto-Parallelization on Graphics Coprocessing Architecture

Guodong Han, Chenggang Zhang, King Tin Lam, Cho-Li Wang

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Java, nVidia, Performance, Tesla M2050

September 27, 2013 by hgpu

Multi-Scale, Multi-Level, Heterogeneous Features Extraction and Classification of Volumetric Medical Images

Shuai Li, Qinping Zhao, Shengfa Wang, Aimin Hao, Hong Qin

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Tags: Algorithms, CUDA, Diffusion tensor, Image processing, nVidia, nVidia GeForce GTX 330 M

September 27, 2013 by hgpu

Trellis: Portability Across Architectures with a High-level Framework

Lukasz G. Szafaryn, Todd Gamblin, Bronis R. de Supinski, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Tesla C2050

September 27, 2013 by hgpu

OpenCL Task Partitioning in the Presence of GPU Contention

Dominik Grewe, Zheng Wang, and Michael F.P. O'Boyle

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Tags: Computer science, Heterogeneous systems, Intel, Intel HD Graphics 4000, Machine learning, OpenCL, Task scheduling

September 25, 2013 by hgpu

Large Graphs on multi-GPUs

Enrico Mastrostefano

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla X2090, Thesis

September 25, 2013 by hgpu

Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

George Ungureanu

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Heterogeneous systems, Image processing, nVidia, Thesis

September 25, 2013 by hgpu

Fast k-NNG construction with GPU-based quick multi-select

Ivan Komarov, Ali Dashti, Roshan D'Souza

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Tags: Algorithms, Bioinformatics, Clustering, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Tesla C2050

September 25, 2013 by hgpu

The density matrix renormalization group algorithm on kilo-processor architectures: implementation and trade-offs

Csaba Nemes, Gergely Barcza, Zoltan Nagy, Ors Legeza, Peter Szolgay

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Tags: Algorithms, Condensed matter, CUDA, FPGA, Numerical Analysis, nVidia, nVidia GeForce GTX 570, Physics, Tesla K20

September 25, 2013 by hgpu

Evaluation of autoparallelization toolkits for commodity graphics hardware

David Williams, Valeriu Codreanu, Po Yang, Baoquan Liu, Feng Dong, Burhan Yasar, Babak Mahdian, Alessandro Chiarini, Xia Zhao, Jos B.T.M. Roerdink

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenACC, Performance

September 24, 2013 by hgpu

Pipeline strategies to accelerate range query processing on a multi-GPU environment

Ricardo J. Barrientos

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Tags: Algorithms, Computer science, CUDA, Image recognition, nVidia, Tesla M2070

September 24, 2013 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

OpenCL Parallel Programming Development Cookbook

GPU-TLS: An Efficient Runtime for Speculative Loop Parallelization on GPUs

Java with Auto-Parallelization on Graphics Coprocessing Architecture

Multi-Scale, Multi-Level, Heterogeneous Features Extraction and Classification of Volumetric Medical Images

Trellis: Portability Across Architectures with a High-level Framework

OpenCL Task Partitioning in the Presence of GPU Contention

Large Graphs on multi-GPUs

Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

Fast k-NNG construction with GPU-based quick multi-select

The density matrix renormalization group algorithm on kilo-processor architectures: implementation and trade-offs

Evaluation of autoparallelization toolkits for commodity graphics hardware

Pipeline strategies to accelerate range query processing on a multi-GPU environment

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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