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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

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

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

An Interrupt-Driven Work-Sharing For-Loop Scheduler

Georgios Rokos, Gerard J. Gorman, Paul H. J. Kelly

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Tags: Computer science, Intel Xeon Phi, OpenMP, Package

May 19, 2015 by hgpu

A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems

Sparsh Mittal and Jeffrey S. Vetter

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Tags: 3D memory, bandwidth compression, cache, classification, cpu, GPU, HPC, main memory, NVM, Review

May 18, 2015 by sparsh0mittal

A Fast and Rigorously Parallel Surface Voxelization Technique for GPU-Accelerated CFD Simulations

C. F. Janssen, N. Koliha, T. Rung

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Tags: Algorithms, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX Titan, Tessellation, Voxelization

May 16, 2015 by hgpu

Multi-GPU Support on Single Node Using Directive-Based Programming Model

Rengan Xu, Xiaonan Tian, Sunita Chandrasekaran, Barbara Chapman

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Tags: Computer science, Heterogeneous systems, nVidia, OpenACC, OpenMP, Tesla K20

May 16, 2015 by hgpu

Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Ayman Tarakji, David Hebbeker, Lyubomir Georgiev

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Tags: AMD FirePro S10000, AMD FirePro S7000, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla C2050

May 16, 2015 by hgpu

Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs

George Teodoro, Tahsin Kurc, Guilherme Andrade, Jun Kong, Renato Ferreira, Joel Saltz

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, Performance, Tesla K20

May 16, 2015 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

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high performance computing on graphics processing units: hgpu.org

Applications

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

U-Net: Convolutional Networks for Biomedical Image Segmentation

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

An Interrupt-Driven Work-Sharing For-Loop Scheduler

A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems

A Fast and Rigorously Parallel Surface Voxelization Technique for GPU-Accelerated CFD Simulations

Multi-GPU Support on Single Node Using Directive-Based Programming Model

Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

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