high performance computing on graphics processing units: hgpu.org

Jeffrey S. Vetter, Richard Glassbrook, Jack Dongarra, Karsten Schwan, Bruce Loftis, Stephen McNally, Jeremy Meredith, James Rogers, Philip Roth Kyle Spafford, Sudhakar Yalamanchili

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Tags: Computer science, Hardware Architecture, Heterogeneous systems, nVidia, Tesla M2070

November 7, 2011 by hgpu

Performance Portability of a GPU Enabled Factorization with the DAGuE Framework

George Bosilca, Aurelien Bouteiller, Thomas Herault, Pierre Lemarinier, Narapat Ohm Saengpatsa, Stanimire Tomov, Jack J. Dongarra

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Tags: Computer science, Factorization, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla C1060, Tesla C2050, Tesla S1070

November 3, 2011 by hgpu

A shared file system abstraction for heterogeneous architectures

Mark Silberstein, Idit Keidar

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Tags: Computer science, Heterogeneous systems, Operating systems

November 2, 2011 by hgpu

Quantum chemical many-body theory on heterogeneous nodes

A. Eugene DePrince, Jeff R. Hammond

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Tags: Algorithms, Computational chemistry, CUBLAS, CUDA, Heterogeneous systems, nVidia, Presentation, Tesla C1060, Tesla C2050

November 1, 2011 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

Creating HW/SW co-designed MPSoPC’s from high level programming models

A translator framework for Dynamic Programming problems

Compiling for a heterogeneous vector image processor

Many-body quantum chemistry on graphics processing units

Automatic transformation and optimization of applications on GPUs and GPU clusters

GPU Cluster with MATLAB

High-Level Design for FPGA-based Multiprocessor Accelerators

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Keeneland: Bringing heterogeneous GPU computing to the computational science community

Performance Portability of a GPU Enabled Factorization with the DAGuE Framework

A shared file system abstraction for heterogeneous architectures

Quantum chemical many-body theory on heterogeneous nodes

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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