high performance computing on graphics processing units: hgpu.org

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CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Edans Flavius O. Sandes, Alba Cristina M.A. de Melo

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, Sequence alignment, Smith-Waterman algorithm

February 27, 2011 by hgpu

Size Matters: Space/Time Tradeoffs to Improve GPGPU Applications Performance

Abdullah Gharaibeh, Matei Ripeanu

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Sequence alignment, Short read mapping, Suffix trees

February 27, 2011 by hgpu

Accelerating CUDA Graph Algorithms at Maximum Warp

Sungpack Hong, Sang Kyun Kim, Tayo Oguntebi, Kunle Olukotun

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, Package, Performance, Programming techniques

February 27, 2011 by hgpu

A Domain-Specific Approach To Heterogeneous Parallelism

Hassan Chafi, Arvind K. Sujeeth, Kevin J. Brown, HyoukJoong Lee, Anand R. Atreya, Kunle Olukotun

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia GeForce GTX 275

February 27, 2011 by hgpu

StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

Cedric Augonnet, Samuel Thibault, Raymond Namyst

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Tags: Computer science, CUDA, Distributed computing, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Package, Performance

February 26, 2011 by hgpu

Real-Time Approaches to Computer Vision

Ron Tal

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Tags: Algorithms, Computer science, Computer vision, CUDA, FPGA, nVidia

February 26, 2011 by hgpu

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Rajesh Bordawekar, Uday Bondhugula, Ravi Rao

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Performance, Programming techniques

February 26, 2011 by hgpu

GPU-Based Foreground-Background Segmentation Using an Extended Colinearity Criterion

Andreas Griesser, Stefaan De Roeck, Alexander Neubeck, Luc Van Gool

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Tags: Cg, Computer vision, Image processing, nVidia, nVidia GeForce 6800 GT, Real-time graphics

February 26, 2011 by hgpu

Concurrent GPU Programming

Lesley Northam

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 M GTX, Programming techniques, Review

February 26, 2011 by hgpu

Efficient GPU-Accelerated Elastic Image Registration

Daniel Ruijters, Bart M. ter Haar Romeny, Paul Suetens

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Tags: Image processing, Image registration, Medicine, nVidia, nVidia Quadro FX 3500, OpenGL

February 26, 2011 by hgpu

Handbook of open source tools

Sandeep Koranne

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, Pthreads

February 26, 2011 by hgpu

Real-time blood flow visualization using the graphics processing unit

Owen Yang, David Cuccia, Bernard Choi

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Tags: CUDA, Image processing, Medicine, nVidia, nVidia GeForce 8800 GTS, Optics, Package

February 26, 2011 by hgpu

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

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high performance computing on graphics processing units: hgpu.org

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Size Matters: Space/Time Tradeoffs to Improve GPGPU Applications Performance

Accelerating CUDA Graph Algorithms at Maximum Warp

A Domain-Specific Approach To Heterogeneous Parallelism

StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

Real-Time Approaches to Computer Vision

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

GPU-Based Foreground-Background Segmentation Using an Extended Colinearity Criterion

Concurrent GPU Programming

Efficient GPU-Accelerated Elastic Image Registration

Handbook of open source tools

Real-time blood flow visualization using the graphics processing unit

Recent source codes

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

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