high performance computing on graphics processing units: hgpu.org

Thomas C.P. Chau, Maciej Kurek, James S. Targett, Jake Humphrey, George Skouroupathis, Alison Eele, Jan Maciejowski, Benjamin Cope, Kathryn Cobden, Philip Leong, Peter Y.K. Cheung, Wayne Luk

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Tags: Algorithms, Computer science, CUDA, FPGA, Machine learning, nVidia, Package, Tesla C2070

May 29, 2014 by hgpu

Engineering a static verification tool for GPU kernels

Ethel Bardsley, Adam Betts, Nathan Chong, Peter Collingbourne, Pantazis Deligiannis, Alastair F. Donaldson, Jeroen Ketema, Daniel Liew, Shaz Qadee

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Tags: Computer science, CUDA, nVidia, OpenCL, Package, Python

May 25, 2014 by hgpu

Real-time Image Processing on Low Cost Embedded Computers

Sunil Shah

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Tags: ARM, Computer vision, Image processing, OpenCV, Package, Performance, Thesis

May 15, 2014 by hgpu

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Christoph Kessler, Usman Dastgeer, Lu Li

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Review, Tesla C2050

May 15, 2014 by hgpu

Build and Travel KD-Tree with CUDA

Meng Zhou

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Tags: 3D Graphics and Realism, Computer science, CUDA, KD-tree, nVidia, nVidia GeForce GTX 780 Ti, Package, Raytracing

May 14, 2014 by hgpu

Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink

Patrick Charrier, Mariusz Klimek, Christian Steinmetz, Dietmar Hildenbrand

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, OpenCL, Package

May 12, 2014 by hgpu

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

Brice Goglin

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Package, Xeon Phi

May 7, 2014 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Packages

Medusa: A Parallel Graph Processing System on Graphics Processors

A Fast Batched Cholesky Factorization on a GPU

Mapping parallel programs to heterogeneous multi-core systems

Loo.py: transformation-based code generation for GPUs and CPUs

An implementation of a reordering approach for increasing the product of diagonal entries in a sparse matrix

SMCGen: Generating Reconfigurable Design for Sequential Monte Carlo Applications

Engineering a static verification tool for GPU kernels

Real-time Image Processing on Low Cost Embedded Computers

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Build and Travel KD-Tree with CUDA

Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

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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