high performance computing on graphics processing units: hgpu.org

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Advanced Video Coding on CPUs and GPUs: Parallelization and RD Analysis

Svetislav Momcilovic, Aleksandar Ilic, Nuno Roma, Leonel Sousa

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Tags: Algorithms, Compression, CUDA, H.264/AVC, Image processing, nVidia, Signal processing, Video encoding

February 25, 2013 by hgpu

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

Ruibang Luo, Thomas Wong, Jianqiao Zhu, Chi-Man Liu, Edward Wu, Lap-Kei Lee, Haoxiang Lin, Wenjuan Zhu, David W. Cheung, Hing-Fung Ting, Siu-Ming Yiu, Chang Yu, Yingrui Li, Ruiqiang Li, Tak-Wah Lam

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, Package, Tesla C2070, Tesla M2050

February 25, 2013 by hgpu

Graphics Card as a Cheap Supercomputer

Jan Prikryl

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, Overview, Package

February 25, 2013 by hgpu

Future of GPGPU Micro-Architectural Parameters

Cedric Nugteren, Gert-Jan van den Braak, Henk Corporaal

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Tags: Computer science, Overview, Performance

February 25, 2013 by hgpu

Multi-GPU Computing for Achieving Speedup in Real-time Aggregate Risk Analysis

A. K. Bahl, O. Baltzer, A. Rau-Chaplin, B. Varghese, A. Whiteway

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Tags: Algorithms, CUDA, Finance, nVidia, Stochastic simulation, Tesla C2075, Tesla M2090

February 23, 2013 by hgpu

Can PCM Benefit GPU? Reconciling Hybrid Memory Design with GPU Massive Parallelism for Energy Efficiency

Bin Wang, Bo Wu, Dong Li, Xipeng Shen, Weikuan Yu, Yizheng Jiao, Jeffrey Vetter

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Tags: Computer science, GPGPU-sim, Memory, Performance

February 23, 2013 by hgpu

Efficient Parallel and External Matching

Marcel Birn, Vitaly Osipov, Peter Sanders, Christian Schulz, Nodari Sitchinava

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, MapReduce, Memory model, nVidia, nVidia GeForce GTX 480

February 23, 2013 by hgpu

Adaptive Hardware-accelerated Terrain Tessellation

Albert Cervin

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Tags: Computer science, Rendering, Tessellation, Thesis

February 23, 2013 by hgpu

Parallel Computer Vision: Person Data Extraction

Lang Christian

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 460, Thesis

February 23, 2013 by hgpu

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Junjie Lai, Andre Seznec

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 680, Optimization, Performance

February 22, 2013 by hgpu

An efficient scheduling scheme using estimated execution time for heterogeneous computing systems

Hong Jun Choi, Dong Oh Son, Seung Gu Kang, Jong Myon Kim, Hsien-Hsin Lee, Cheol Hong Kim

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8500 GT

February 22, 2013 by hgpu

A Parallel Active-Set Method for Solving Frictional Contact Problems

Joshua Alexander Litven

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 580, Physics, Thesis

February 22, 2013 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Advanced Video Coding on CPUs and GPUs: Parallelization and RD Analysis

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

Graphics Card as a Cheap Supercomputer

Future of GPGPU Micro-Architectural Parameters

Multi-GPU Computing for Achieving Speedup in Real-time Aggregate Risk Analysis

Can PCM Benefit GPU? Reconciling Hybrid Memory Design with GPU Massive Parallelism for Energy Efficiency

Efficient Parallel and External Matching

Adaptive Hardware-accelerated Terrain Tessellation

Parallel Computer Vision: Person Data Extraction

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

An efficient scheduling scheme using estimated execution time for heterogeneous computing systems

A Parallel Active-Set Method for Solving Frictional Contact Problems

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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