high performance computing on graphics processing units: hgpu.org

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clOpenCL – Supporting Distributed Heterogeneous Computing in HPC Clusters

Albano Alves, Jose Rufino, Antonio Pina, Luis Paulo Santos

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Tags: Cluster computing, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, OpenCL

November 29, 2012 by hgpu

Formal Semantics of Heterogeneous CUDA-C: A Modular Approach with Applications

Chris Hathhorn, Michela Becchi, William L. Harrison, Adam Procter

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Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Programming Languages

November 28, 2012 by hgpu

Optimizing 3D Convolutions for Wavelet Transforms on CPUs with SSE Units and GPUs

Brice Videau, Vania Marangozova-Martin, Luigi Genovese, Thierry Deutsch

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, nVidia, OpenCL, Optimization, Tesla C2070, Wavelet

November 27, 2012 by hgpu

High Performance Radiation Transport Simulations: Preparing for TITAN

C. Baker, G. Davidson, T. M. Evans, S. Hamilton, J. Jarrell, W. Joubert

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Tesla X2090

November 26, 2012 by hgpu

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System

Qingyu Meng, Alan Humphrey, Martin Berzins

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, MPI, nVidia, nVidia GeForce GTX 570, Task scheduling, Tesla C2070

November 24, 2012 by hgpu

CoreTSAR: Task Scheduling for Accelerator-aware Runtimes

Thomas R. W. Scogland, Wu-chun Feng, Barry Rountree, Bronis R. de Supinski

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C2070

November 22, 2012 by hgpu

Automatic generation of software pipelines for heterogeneous parallel systems

Jacques A. Pienaar, Srimat Chakradhar, Anand Raghunathan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C1060

November 22, 2012 by hgpu

ValuePack: value-based scheduling framework for CPU-GPU clusters

Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar

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Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Tesla C2050

November 21, 2012 by hgpu

Pattern Recognition with OpenCL Heterogeneous Platform

Jordan Vrtanoski, Toni Draganov Stojanovski

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, Neural networks, OpenCL, Pattern recognition

November 21, 2012 by hgpu

Accelerating MapReduce on a coupled CPU-GPU architecture

Linchuan Chen, Xin Huo, Gagan Agrawal

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Tags: APU, ATI, ATI Radeon HD 6550, Computer science, Data mining, Heterogeneous systems, Machine learning, MapReduce, OpenCL

November 20, 2012 by hgpu

High locality and increased intra-node parallelism for solving finite element models on GPUs by novel element-by-element implementation

Imre Kiss, Zsolt Badics, Szabolcs Gyimothy, Jozsef Pavo

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Tags: Computer science, CUDA, FEM, Finite element method, Heterogeneous systems, nVidia, nVidia GeForce GTX 590

November 18, 2012 by hgpu

Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Mayank Daga, Mark Nutter

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Tags: APU, ATI, ATI Radeon HD 7660, ATI Radeon HD 7970, Computer science, Databases, Heterogeneous systems, OpenCL

November 18, 2012 by hgpu

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

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

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

clOpenCL – Supporting Distributed Heterogeneous Computing in HPC Clusters

Formal Semantics of Heterogeneous CUDA-C: A Modular Approach with Applications

Optimizing 3D Convolutions for Wavelet Transforms on CPUs with SSE Units and GPUs

High Performance Radiation Transport Simulations: Preparing for TITAN

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System

CoreTSAR: Task Scheduling for Accelerator-aware Runtimes

Automatic generation of software pipelines for heterogeneous parallel systems

Pattern Recognition with OpenCL Heterogeneous Platform

Accelerating MapReduce on a coupled CPU-GPU architecture

High locality and increased intra-node parallelism for solving finite element models on GPUs by novel element-by-element implementation

Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Recent source codes

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

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

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

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

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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