high performance computing on graphics processing units: hgpu.org

Applications

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Parallel and Improved PageRank Algorithm for GPU-CPU Collaborative Environment

Prasann Choudhari, Eikshith Baikampadi, Paresh Patil, Sanket Gadekar

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Tags: Algorithms, Computer science, CUDA, nVidia

May 22, 2015 by hgpu

Toward GPUs being mainstream in analytic processing: An initial argument using simple scan-aggregate queries

Jason Power, Yinan Li, Mark D. Hill, Jignesh M. Patel, David A. Wood

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Tags: Algorithms, AMD Radeon R7 240, ATI, ATI Radeon HD 7970, Computer science, Databases, Heterogeneous systems, OpenCL

May 22, 2015 by hgpu

Accelerating SWHE based PIRs using GPUs

Wei Dai, Yarkin Doroz, Berk Sunar

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Tags: Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 690, Security

May 22, 2015 by hgpu

A Performance and Scalability Analysis of the Tsunami Simulation EasyWave for Different Multi-Core Architectures and Programming Models

Steffen Christgau, Johannes Spazier, Bettina Schnor

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Tags: CUDA, Earth and Space Sciences, Geoscience, Intel Xeon Phi, MPI, nVidia, OpenMP, Package, Performance, Tesla K40

May 20, 2015 by hgpu

Physically Based Rendering: Implementation of Path Tracer

Vinh Truong

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, OpenGL, Raytracing, Rendering, Thesis

May 20, 2015 by hgpu

Kalman Filter Tracking on Parallel Architectures

Giuseppe Cerati, Peter Elmer, Steven Lantz, Kevin McDermott, Dan Riley, Matevz Tadel, Peter Wittich, Frank Wurthwein, Avi Yagil

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Tags: Instrumentation and Detectors, Intel Xeon Phi, OpenMP, Physics

May 20, 2015 by hgpu

U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger, Philipp Fischer, Thomas Brox

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Tags: CNN, Computer science, CUDA, Deep learning, Image processing, Medicine, Microscopy, Neural networks, nVidia, nVidia GeForce GTX Titan, Package

May 20, 2015 by hgpu

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

Gordon Inggs, David B. Thomas, Wayne Luk

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Tags: AMD FirePro W5000, ATI, Computational finance, Computer science, Finance, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia Grid K2, nVidia Quadro K4000, OpenCL, Option pricing, Performance

May 20, 2015 by hgpu

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Geoffrey Ndu, Javier Navaridas, Mikel Lujan

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Tags: Benchmarking, Computer science, FPGA, OpenCL, Package, Performance

May 19, 2015 by hgpu

Optimizing Full Correlation Matrix Analysis of fMRI Data on Intel Xeon Phi Coprocessors

Yida Wang, Michael Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Ted Willke

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Tags: Algorithms, Computer science, Intel Xeon Phi, Magnetic resonance imaging, MRI, Performance

May 19, 2015 by hgpu

Use of modern GPUs in Design Optimization

M.H. Aissa, T. Verstraete, C. Vuik

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Tags: Computer science, Optimization, Review

May 19, 2015 by hgpu

A GPU-accelerated Navier-Stokes Solver for Steady Turbomachinery Simulations

Mohamed Hassanine Aissa, Tom Verstraete, C. Vuik

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Tags: Fluid dynamics, nVidia

May 19, 2015 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

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high performance computing on graphics processing units: hgpu.org

Applications

Parallel and Improved PageRank Algorithm for GPU-CPU Collaborative Environment

Toward GPUs being mainstream in analytic processing: An initial argument using simple scan-aggregate queries

Accelerating SWHE based PIRs using GPUs

A Performance and Scalability Analysis of the Tsunami Simulation EasyWave for Different Multi-Core Architectures and Programming Models

Physically Based Rendering: Implementation of Path Tracer

Kalman Filter Tracking on Parallel Architectures

U-Net: Convolutional Networks for Biomedical Image Segmentation

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Optimizing Full Correlation Matrix Analysis of fMRI Data on Intel Xeon Phi Coprocessors

Use of modern GPUs in Design Optimization

A GPU-accelerated Navier-Stokes Solver for Steady Turbomachinery Simulations

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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