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Taming the complexities of the C11 and OpenCL memory models

John Wickerson, Mark Batty

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Tags: Computer science, Heterogeneous systems, Memory model, OpenCL, Package

January 23, 2015 by hgpu

CHO: A Benchmark Suite for OpenCL-based FPGA Accelerators

Geoffrey Ndu, Mikel Lujan, Javier Navaridas

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Tags: Benchmarking, Computer science, FPGA, OpenCL, Package

January 8, 2015 by hgpu

Subdivision Surface Evaluation as Sparse Matrix-Vector Multiplication

Michael Driscoll

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Tags: 3D Graphics and Realism, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sparse matrix

January 5, 2015 by hgpu

PyFAI: a Python library for high performance azimuthal integration on GPU

Jerome Kieffer, Giannis Ashiotis

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Tags: Astrophysics, ATI, ATI FirePro V7800, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, nVidia, nVidia GeForce GTX 750 Ti, OpenCL, Package, PyOpenCL, Python, Tesla K20

December 22, 2014 by hgpu

Optimising Hydrodynamics applications for the Cray XC30 with the application tool suite

W. P. Gaudin, A. C. Mallinson, O. Perks, J. A. Herdman, D. A. Beckingsale, J. M. Levesque, M. Boulton, S. McIntosh-Smith, S. A. Jarvis

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Tags: CUDA, Fluid dynamics, MPI, nVidia, OpenACC, OpenCL, Package, Tesla K20

December 18, 2014 by hgpu

Risk Estimation Without Using Stein’s Lemma — Application to Image Denoising

Sagar Venkatesh Gubbi, Chandra Sekhar Seelamantula

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Tags: ATI, ATI Radeon HD 7950, Computer vision, Image processing, OpenCL, Package, Signal denoising

December 9, 2014 by hgpu

Scalable Verification Techniques for Data-Parallel Programs

Nathan Yong Seng Chong

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Tags: ARM, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, OpenCL, Package, Tesla M2050, Thesis

November 25, 2014 by hgpu

CL2QCD – Lattice QCD based on OpenCL

Owe Philipsen, Christopher Pinke, Alessandro Sciarra, Matthias Bach

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Tags: AMD FirePro S10000, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Physics, QCD, Tesla K40

November 20, 2014 by hgpu

Using Graphics Processing Units to solve the classical N-body problem in physics and astrophysics

Mario Spera

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Tags: Astrophysics, CUDA, Electrodynamics, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, QCD

November 20, 2014 by hgpu

Mobile GPGPU Acceleration of Embodied Robot Simulation

Simon Jones, Matthew Studley, Alan Winfield

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Tags: Computer science, OpenCL, Package, Robotics

November 16, 2014 by hgpu

A Performance Comparison of Sort and Scan Libraries for GPUs

Bruce Merry

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Tags: Algorithms, AMD Radeon R9 270, ATI, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sorting, Tesla K40

October 20, 2014 by hgpu

GPU-based NSEC3 Hash Breaking

Matthaus Wander, Lorenz Schwittmann, Christopher Boelmann, Torben Weis

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Tags: ATI, ATI Radeon HD 7970, Computer science, nVidia, nVidia GeForce GTX 690, OpenCL, Package, Security

September 19, 2014 by hgpu

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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high performance computing on graphics processing units: hgpu.org

Programming

Taming the complexities of the C11 and OpenCL memory models

CHO: A Benchmark Suite for OpenCL-based FPGA Accelerators

Subdivision Surface Evaluation as Sparse Matrix-Vector Multiplication

PyFAI: a Python library for high performance azimuthal integration on GPU

Optimising Hydrodynamics applications for the Cray XC30 with the application tool suite

Risk Estimation Without Using Stein’s Lemma — Application to Image Denoising

Scalable Verification Techniques for Data-Parallel Programs

CL2QCD – Lattice QCD based on OpenCL

Using Graphics Processing Units to solve the classical N-body problem in physics and astrophysics

Mobile GPGPU Acceleration of Embodied Robot Simulation

A Performance Comparison of Sort and Scan Libraries for GPUs

GPU-based NSEC3 Hash Breaking

Recent source codes

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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