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Automatic run-time mapping of polyhedral computations to heterogeneous devices with memory-size restrictions

Yuri Torres, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, nVidia GeForce GTX 680

October 12, 2013 by hgpu

Dandelion: a Compiler and Runtime for Heterogeneous Systems

Christopher J. Rossbach, Yuan Yu, Jon Currey, Jean-Philippe Martin, Dennis Fetterly

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20

October 12, 2013 by hgpu

A Parallel Intermediate Representation for Embedded Languages

Ivar Lang

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Source codes

Tags: Computer science, Data parallelism, nVidia, OpenCL, Package, Tesla M2050, Thesis

October 10, 2013 by hgpu

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

Daniel N. Benedetti, W. Randolph Franklin, Wenli Li

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Tags: Algorithms, Compression, CUDA, Differential equations, Image processing, nVidia, Partial differential equations, PDEs, Thrust

October 10, 2013 by hgpu

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

You-Liang Zhu, Hong Liu, Zhan-Wei Li, Hu-Jun Qian, Giuseppe Milano, Zhong-Yuan Lu

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Tags: Chemical Physics, Computational Physics, CUDA, Molecular simulation, nVidia, nVidia GeForce GTX 580, Phase transition, Physics, Soft Condensed Matter, Tesla K20

October 10, 2013 by hgpu

Direct deconvolution of radio synthesis images using L1 minimisation

Stephen J. Hardy

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Tags: Astrophysics, CUDA, Image reconstruction, Instrumentation and Methods for Astrophysics, nVidia, Package, Tesla M2050

October 10, 2013 by hgpu

Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

Blesson Varghese, Andrew Rau-Chaplin

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Tags: Computational Engineering, Computer science, CUDA, Finance, nVidia, Risk Management, Tesla C2075

October 10, 2013 by hgpu

Scalable Fast Multipole Methods on Heterogeneous Architecture

Q. Hu

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, Heterogeneous systems, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Tesla C1060, Tesla C2050, Thesis

October 9, 2013 by hgpu

Performance Analysis of a Large Memory Application on Multiple Architectures

P.M.Kogge

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Tags: Benchmarking, Heterogeneous systems, nVidia, nVidia Tesla, Performance

October 9, 2013 by hgpu

Enabling the use of Heterogeneous Computing for Bioinformatics

Ramakrishna Bijanapalli Chakri

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Tags: Bioinformatics, Biology, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Smith-Waterman algorithm, Thesis

October 8, 2013 by hgpu

Stressing the BER simulation of LDPC codes in the error floor region using GPU clusters

Gabriel Falcao, Joao Andrade, Vitor Silva, Shinichi Yamagiwa, Leonel Sousa

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Tags: Computer science, CUDA, GPU cluster, Monte Carlo simulation, nVidia, Parity-check codes, Tesla M2050

October 8, 2013 by hgpu

Parallel and Distributed Implementations of Multiple and Two-Dimensional Pattern Matching Algorithms

Charalampos S. Kouzinopoulos

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 280, String matching, Thesis

October 8, 2013 by hgpu

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

Automatic run-time mapping of polyhedral computations to heterogeneous devices with memory-size restrictions

Dandelion: a Compiler and Runtime for Heterogeneous Systems

A Parallel Intermediate Representation for Embedded Languages

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

Direct deconvolution of radio synthesis images using L1 minimisation

Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

Scalable Fast Multipole Methods on Heterogeneous Architecture

Performance Analysis of a Large Memory Application on Multiple Architectures

Enabling the use of Heterogeneous Computing for Bioinformatics

Stressing the BER simulation of LDPC codes in the error floor region using GPU clusters

Parallel and Distributed Implementations of Multiple and Two-Dimensional Pattern Matching Algorithms

Recent source codes

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

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

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

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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