high performance computing on graphics processing units: hgpu.org

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Issues and challenges in compiling for graphics processors

Norm Rubin

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Tags: Computer science, High-level Languages, Presentation, Review

November 4, 2010 by hgpu

CuPP – A framework for easy CUDA integration

Jens Breitbart

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Tags: Computer science, CUDA, High-level Languages, nVidia, Package

November 4, 2010 by hgpu

Brook for GPUs: Stream Computing on Graphics Hardware

I. Buck, T. Foley, D. Horn, J. Sugerman, K. Mike, H. Pat

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Tags: ATI, ATI Radeon 9800 XT, ATI Stream, Brook, Computer science, High-level Languages, nVidia, nVidia GeForce FX 5900 Ultra, OpenGL, Stream Computing

November 3, 2010 by hgpu

Optimization principles and application performance evaluation of a multithreaded GPU using CUDA

Shane Ryoo, Christopher I. Rodrigues, Sara S. Baghsorkhi, Sam S. Stone, David B. Kirk, Wen-mei W. Hwu

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques

October 27, 2010 by hgpu

PyCUDA: GPU Run-Time Code Generation for High-Performance Computing

Andreas Klockner,Nicolas Pinto,Yunsup Lee,Bryan Catanzaro,Paul Ivanov,Ahmed Fasih

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Tags: Computer science, CUDA, High-level Languages, nVidia, Package

October 27, 2010 by hgpu

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

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

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high performance computing on graphics processing units: hgpu.org

Issues and challenges in compiling for graphics processors

CuPP – A framework for easy CUDA integration

Brook for GPUs: Stream Computing on Graphics Hardware

Optimization principles and application performance evaluation of a multithreaded GPU using CUDA

PyCUDA: GPU Run-Time Code Generation for High-Performance Computing

Recent source codes

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

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

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