high performance computing on graphics processing units: hgpu.org

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Offloading Java to Graphics Processors

Peter Calvert

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 260

October 6, 2011 by hgpu

Parallelisation of Java for Graphics Processors

Peter Calvert

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260, Package, Thesis

October 6, 2011 by hgpu

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Olav Aanes Fagerlund

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 280, OpenCL, Thesis

October 6, 2011 by hgpu

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

Zane W. Bell, Greg G. Davidson, Ed D'Azevedo, Thomas M. Evans, Wayne Joubert, John K. Munro, Jr., Dilip R. Patlolla, Bogdan Vacaliuc

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Tags: Boltzmann equation, CUDA, Heterogeneous systems, nVidia, Package, Physics, Presentation, Python, Tesla M2070

October 6, 2011 by hgpu

Accelerating a climate physics model with OpenCL

Fahad Zafar, Dibyajyoti Ghosh, Lawrence Sebald, Shujia Zhou

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Tags: Earth and Space Sciences, Heterogeneous systems, OpenCL, Physics, Presentation

October 6, 2011 by hgpu

Static GPU threads and an improved scan algorithm

Jens Breitbart

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 280, OpenCL, Performance, Presentation, Programming techniques

October 6, 2011 by hgpu

GPU-based single-cluster algorithm for the simulation of the Ising model

Yukihiro Komura, Yutaka Okabe

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, Physics

October 6, 2011 by hgpu

Connected-component identification and cluster update on graphics processing units

Martin Weigel

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla M2070

October 6, 2011 by hgpu

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Andrew Nere, Atif Hashmi, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image recognition, Neural networks, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Tesla C2050

October 5, 2011 by hgpu

Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations

Paul Richmond, Lars Buesing, Michele Giugliano, Eleni Vasilaki

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Tags: Biology, CUDA, Neuroscience, nVidia, nVidia GeForce GTX 480, Package, Python

October 5, 2011 by hgpu

Performance Analysis and Optimisation of the OP2 Framework on Many-core Architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

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Tags: Benchmarking, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, OpenMP, Partial differential equations, PDEs, Tesla C2050

October 5, 2011 by hgpu

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

Mark Silberstein, Assaf Schuster, John D. Owens

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, Optimization, Package, Performance, Probability, Task scheduling, Tesla C2050

October 5, 2011 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

Programming

Offloading Java to Graphics Processors

Parallelisation of Java for Graphics Processors

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

Accelerating a climate physics model with OpenCL

Static GPU threads and an improved scan algorithm

GPU-based single-cluster algorithm for the simulation of the Ising model

Connected-component identification and cluster update on graphics processing units

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations

Performance Analysis and Optimisation of the OP2 Framework on Many-core Architectures

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

Recent source codes

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

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