high performance computing on graphics processing units: hgpu.org

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Lattice Boltzmann simulations of the permeability and capillary adsorption of cement model microstructures

M. Zalzale, P. J. McDonald

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Tags: CUDA, Lattice Boltzmann model, Materials Science, nVidia, nVidia GeForce GTX 460 M

January 12, 2013 by hgpu

Efficient implementation of data flow graphs on multi-gpu clusters

Vincent Boulos, Sylvain Huet, Vincent Fristot, Luc Salvo, Dominique Houzet

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Tags: Algorithms, CUDA, GPU cluster, Image processing, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 460 M, Signal processing

November 7, 2012 by hgpu

A GPU Accelerated Volumetric Ray Tracer for Incandescent Gas

Andrew Zonenberg, Sylvia Forrest

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Tags: Computer science, CUDA, Fluid simulation, nVidia, nVidia GeForce GTX 460 M, Rendering

December 31, 2011 by hgpu

Embedding OpenCL in C++ for Expressive GPU Programming

Orion Lawlor

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Tags: ATI, ATI Radeon HD 6850, Benchmarking, Code generation, Computer science, GLSL, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 460 M, nVidia GeForce GTX 580, OpenCL, OpenGL, Package

September 23, 2011 by hgpu

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

A Unified Intermediate Representation and Execution Architecture for Heterogeneous and Distributed Neural Simulation

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelLens: Deploying Triton Kernels to C++ Inference Engines

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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high performance computing on graphics processing units: hgpu.org

Lattice Boltzmann simulations of the permeability and capillary adsorption of cement model microstructures

Efficient implementation of data flow graphs on multi-gpu clusters

A GPU Accelerated Volumetric Ray Tracer for Incandescent Gas

Embedding OpenCL in C++ for Expressive GPU Programming

Recent source codes

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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