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A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

Confidentiality Issues on a GPU in a Virtualized Environment

Clementine Maurice, Christoph Neumann, Olivier Heen, Aurelien Francillon

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Tags: Cloud, Computer science, CUDA, nVidia, Security, Tesla K20, Virtualization

February 11, 2014 by hgpu

Exploiting GPU Parallelism to Optimize Real-World Problems

Hasan Furhad, Fahmida Ahmed, Faisal Faruque, Iqbal Hasan Sarker

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Optimization

February 11, 2014 by hgpu

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Vivek K. Pallipuram

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Performance, Tesla K20, Tesla M2075, Thesis

February 11, 2014 by hgpu

Point Rendering in CUDA Path Tracer

Hsuan-Yueh Peng

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Rendering

February 11, 2014 by hgpu

Accurate Cross-Architecture Performance Modeling for Sparse Matrix-Vector Multiplication (SpMV) on GPUs

Ping Guo, Liqiang Wang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Performance, Sparse matrix, Tesla C2050, Tesla K20, Tesla M2090

February 11, 2014 by hgpu

Implementing the Projected Spatial Rich Features on a GPU

Andrew D. Ker

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Tags: Computer science, CUDA, Machine learning, nVidia, Tesla K20

February 11, 2014 by hgpu

Genetically Improved CUDA C++ Software

W. B. Langdon, M. Harman

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Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, nVidia Quadro NVS 290, Package, Tesla C2050, Tesla K20, Tesla T10

February 11, 2014 by hgpu

GPGPU-Assisted Subpixel Tracking Method for Fiducial Markers

Naoki Shibata, Shinya Yamamoto

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Tags: Augmented reality, Computer science, Java, nVidia, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 670, OpenCL

February 9, 2014 by hgpu

Extending the SkelCL Skeleton Library for Stencil Computations on Multi-GPU Systems

Stefan Breuer, Michel Steuwer, Sergei Gorlatch

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Tags: Computer science, nVidia, OpenCL, Tesla S1070

February 9, 2014 by hgpu

GPU-based high-performance computing for radiation therapy

Xun Jia, Peter Ziegenhein, Steve B Jiang

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Tags: CUDA, Medicine, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 570, nVidia GeForce GTX 580, nVidia GeForce GTX 590, Physics, Radiotherapy, Review, Tesla C1060, Tesla C2050, Tesla C2070

February 9, 2014 by hgpu

Fast 2-D Ultrasound Strain Imaging: The Benefits of Using a GPU

Tim Idzenga, Evghenii Gaburov, Willem Vermin, Jan Menssen, Chris L. de Korte

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Tags: Algorithms, CUDA, Image processing, nVidia, OpenMP, Package, Tesla K20, Ultrasound

February 8, 2014 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Exploiting GPU Parallelism to Optimize Real-World Problems

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Point Rendering in CUDA Path Tracer

Accurate Cross-Architecture Performance Modeling for Sparse Matrix-Vector Multiplication (SpMV) on GPUs

Implementing the Projected Spatial Rich Features on a GPU

Genetically Improved CUDA C++ Software

GPGPU-Assisted Subpixel Tracking Method for Fiducial Markers

Extending the SkelCL Skeleton Library for Stencil Computations on Multi-GPU Systems

GPU-based high-performance computing for radiation therapy

Fast 2-D Ultrasound Strain Imaging: The Benefits of Using a GPU

Recent source codes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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