high performance computing on graphics processing units: hgpu.org

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Fast and accurate digital signal processing realized with GPGPU technology

Adam Dabrowski, Pawel Pawlowski, Mateusz Stankiewicz, Filip Misiorek

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Tags: CUDA, nVidia, nVidia Quadro FX 2000, nVidia Quadro FX 580, Signal processing

May 26, 2012 by hgpu

Parallelization of the Local Threshold and Boolean Function Based Edge Detection Algorithm Using CUDA

Raka Jovanovic, Milan Tuba, Dana Simian

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 540 M

May 26, 2012 by hgpu

Using Compute Unified Device Architecture (CUDA) in Parallelizing Different Digital Image Processing Techniques

Mikaela Nadinne A. Silapan

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GT 520 M

May 25, 2012 by hgpu

On the Simulations of Evolution-Communication P Systems with Energy without Antiport Rules for GPUs

Richelle Ann B. Juayong, Francis George C. Cabarle, Henry N. Adorna, Miguel A. Martinez-del-Amor

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Tags: Computer science, CUDA, Membrane computing, nVidia, P systems

May 25, 2012 by hgpu

Effective Sparse Matrix Representation for the GPU Architectures

B. Neelima, Prakash S. Raghavendra

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 525 M, Optimization, Sparse matrix

May 25, 2012 by hgpu

Accelerating In-Memory Graph Database traversal using GPGPUS

Ashwin Raghav Mohan Ganesh

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Tags: Computer science, CUDA, Databases, nVidia, Package

May 25, 2012 by hgpu

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Rohit Sinha, Aayush Prakash, Hiren D. Patel

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Tags: Computer science, CUDA, nVidia, Tesla C2075

May 25, 2012 by hgpu

Java on CUDA architecture

Jan Strnad

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Tags: Computer science, CUDA, Image processing, Java, Linear Algebra, Matrix multiplication, nVidia, Thesis

May 24, 2012 by hgpu

Sparse direct solvers with accelerators over DAG runtimes

Xavier Lacoste, Pierre Ramet, Mathieu Faverge, Yamazaki Ichitaro, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse direct solvers, Tesla T20

May 24, 2012 by hgpu

Tuning a Finite Difference Computation for Parallel Vector Processors

Gerhard Zumbusch

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Tags: Algorithms, Computer science, Finite difference, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenCL, Performance

May 24, 2012 by hgpu

Compiler optimizations for directive-based programming for accelerators

Matias Piispanen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Optimization

May 24, 2012 by hgpu

Fine-Grained Resource Sharing for Concurrent GPGPU Kernels

Chris Gregg, Jonathan Dorn, Kim Hazelwood, Kevin Skadron

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Tags: Computer science, nVidia, nVidia GeForce GTX 460, OpenCL, Programming techniques, Task scheduling

May 24, 2012 by hgpu

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Fast and accurate digital signal processing realized with GPGPU technology

Parallelization of the Local Threshold and Boolean Function Based Edge Detection Algorithm Using CUDA

Using Compute Unified Device Architecture (CUDA) in Parallelizing Different Digital Image Processing Techniques

On the Simulations of Evolution-Communication P Systems with Energy without Antiport Rules for GPUs

Effective Sparse Matrix Representation for the GPU Architectures

Accelerating In-Memory Graph Database traversal using GPGPUS

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Java on CUDA architecture

Sparse direct solvers with accelerators over DAG runtimes

Tuning a Finite Difference Computation for Parallel Vector Processors

Compiler optimizations for directive-based programming for accelerators

Fine-Grained Resource Sharing for Concurrent GPGPU Kernels

Recent source codes

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

CUDAnalyst (CUDA + Analyst)

CodegenBench

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

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