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Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems

Kaibo Wang, Yin Huai, Rubao Lee, Fusheng Wang, Xiaodong Zhang, Joel H. Saltz

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Tags: CUDA, Databases, Image processing, nVidia, nVidia GeForce GTX 580, Tesla M2050

August 2, 2012 by hgpu

A GPU-Computing Approach to Solar Stokes Profile Inversion

Brian J. Harker, Kenneth J. Mighell

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Tags: Astrophysics, CUDA, nVidia, Solar and Stellar Astrophysics, Tesla C1060

August 2, 2012 by hgpu

Interference-driven resource management for GPU-based heterogeneous clusters

Rajat Phull, Cheng-Hong Li, Kunal Rao, Srihari Cadambi, Srimat Chakradhar

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, PC cluster, Performance, Tesla C2050

August 1, 2012 by hgpu

GPU merge path: a GPU merging algorithm

Oded Green, Robert McColl, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Tesla C1060, Tesla C2070

August 1, 2012 by hgpu

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

Neelima Reddy, Raghavendra Prakash, Ram Mohana Reddy

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 470, Sparse matrix

August 1, 2012 by hgpu

accULL: An User-directed Approach to Heterogeneous Programming

Ruyman Reyes, Ivan Lopez, Juan J. Fumero, Francisco de Sande

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Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Package, Python, Tesla C1060, Tesla C2050

July 31, 2012 by hgpu

Parallel programming on GPU using Intel Array Building Blocks

Chatura A. Ettigi

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 260 M, Programming techniques, Thesis

July 31, 2012 by hgpu

On Binaural Spatialization and the Use of GPGPU for Audio Processing

Davide Andrea Mauro

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Tags: Acoustics, CUDA, DSP, FFT, nVidia, nVidia GeForce 9400 M GS, OpenCL, Signal processing, Thesis

July 31, 2012 by hgpu

Application of the Mean Field Methods to MRF Optimization in Computer Vision

Masaki Saito, Takayuki Okatani, Koichiro Deguchi

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480, OpenMP

July 31, 2012 by hgpu

High-Performance Online Spatial and Temporal Aggregations on Multi-core CPUs and Many-Core GPUs

Jianting Zhang, Simin You, Le Gruenwald

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Tags: Computer science, CUDA, Databases, nVidia, nVidia Quadro FX 6000

July 29, 2012 by hgpu

Sigma*: Symbolic Learning of Stream Filters

Matko Botincan, Domagoj Babic

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 460

July 29, 2012 by hgpu

A Novel GPU Implementation of Eigen Analysis for Risk Management

Mustafa U. Torun, Ali N. Akansu

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Tags: CUDA, Filtering, Finance, nVidia, Risk Management, Tesla C2070

July 29, 2012 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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems

A GPU-Computing Approach to Solar Stokes Profile Inversion

Interference-driven resource management for GPU-based heterogeneous clusters

GPU merge path: a GPU merging algorithm

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

accULL: An User-directed Approach to Heterogeneous Programming

Parallel programming on GPU using Intel Array Building Blocks

On Binaural Spatialization and the Use of GPGPU for Audio Processing

Application of the Mean Field Methods to MRF Optimization in Computer Vision

High-Performance Online Spatial and Temporal Aggregations on Multi-core CPUs and Many-Core GPUs

Sigma*: Symbolic Learning of Stream Filters

A Novel GPU Implementation of Eigen Analysis for Risk Management

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

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

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