high performance computing on graphics processing units: hgpu.org

A. Lonardo, F. Ameli, R. Ammendola, A. Biagioni, O. Frezza, G. Lamanna, F. Lo Cicero, M. Martinelli, P. S. Paolucci, E. Pastorelli, L. Pontisso, D. Rossetti, F. Simeone, F. Simula, M. Sozzi, L. Tosoratto, P. Vicini

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Tags: CUDA, FPGA, Instrumentation and Detectors, nVidia, Physics, Tesla M2070

June 16, 2014 by hgpu

Toward OpenCL Automatic Multi-Device Support

Henry Sylvain, Alexandre Denis, Denis Barthou, Marie-Christine Counilh, Raymond Namyst

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Tesla M2075

June 15, 2014 by hgpu

Evaluating CP2K on Exascale Hardware: Intel Xeon Phi

Fiona Reid, Iain Bethune

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Tags: Chemistry, Intel Xeon Phi, Molecular dynamics, MPI, OpenMP

June 15, 2014 by hgpu

Airborne radar clutter simulation using GPU (CUDA)

Priyanka A P, Channabasappa Baligar

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Tags: CUDA, nVidia, nVidia Quadro FX 380, Signal processing

June 15, 2014 by hgpu

A Parallel Algorithm of PCA-SIFT Based on CUDA

Ping Zhang, Yongqi Sun, Hao Shen, Rui Zhang

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 240, OpenCV, Pattern recognition, SIFT

June 15, 2014 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

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

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high performance computing on graphics processing units: hgpu.org

Applications

A CUDA based Solution to the Multidimensional Knapsack Problem Using the Ant Colony Optimization

HAM – Heterogenous Active Messages for Efficient Offloading on the Intel Xeon Phi

GPU Implementation of Bayesian Neural Network Construction for Data-Intensive Applications

Synergia CUDA: GPU-accelerated accelerator modeling package

Divide and Conquer G-Buffer Ray Tracing

An in-depth performance analysis of irregular workloads on VLIW APU

Improved Distance Weighted GPU-based 3D Ultrasound Reconstruction Methods

NaNet: a Low-Latency, Real-Time, Multi-Standard Network Interface Card with GPUDirect Features

Toward OpenCL Automatic Multi-Device Support

Evaluating CP2K on Exascale Hardware: Intel Xeon Phi

Airborne radar clutter simulation using GPU (CUDA)

A Parallel Algorithm of PCA-SIFT Based on CUDA

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

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

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