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Creating HW/SW co-designed MPSoPC’s from high level programming models

Eugene Cartwright, Sen Ma, David Andrews, Miaoqing Huang

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, Operating systems, Pthreads

November 12, 2011 by hgpu

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

S.J. Pennycook, S.D. Hammond, S.A. Jarvis, G.R. Mudalige

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9400 GT, Operating systems, Performance, Tesla C1060, Tesla C2050, Tesla T10

November 8, 2011 by hgpu

A shared file system abstraction for heterogeneous architectures

Mark Silberstein, Idit Keidar

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Tags: Computer science, Heterogeneous systems, Operating systems

November 2, 2011 by hgpu

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Amnon Barak, Amnon Shiloh

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Source codes

Tags: APU, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

October 24, 2011 by hgpu

Efficient Synchronization Primitives for GPUs

Jeff A. Stuart, John D. Owens

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, Operating systems

October 21, 2011 by hgpu

Operating Systems Challenges for GPU Resource Management

Shinpei Kato, Scott Brandt, Yutaka Ishikawa, Ragunathan (Raj) Rajkumar

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Tags: Computer science, CUDA, GPU cluster, nVidia, OpenCL, Operating systems, Virtualization

October 15, 2011 by hgpu

PTask: Operating System Abstractions To Manage GPUs as Compute Devices

Christopher J. Rossbach, Jon Currey, Mark Silberstein, Baishakhi Ray, Emmett Witchel

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Tags: Computer science, CUDA, HLSL, nVidia, nVidia GeForce GT 230, nVidia GeForce GTX 470, nVidia GeForce GTX 580, OpenCL, Operating systems, Performance, Programming techniques

October 2, 2011 by hgpu

Real-Time Handling of GPU Interrupts in LITMUSRT

Glenn A. Elliott, Chih-Hao Sun, and James H. Anderson

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, Operating systems

September 30, 2011 by hgpu

Supporting GPU sharing in cloud environments with a transparent runtime consolidation framework

Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar

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Tags: Algorithms, Cloud, Computer science, CUDA, nVidia, Operating systems, Performance, Tesla C2050, Virtualization

September 20, 2011 by hgpu

Performing with CUDA

William B. Langdon

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Tags: Computer science, CUDA, nVidia, Operating systems, Performance, Review, Software Engineering, Tutorial

September 15, 2011 by hgpu

The case for VOS: the vector operating system

Vijay Vasudevan, David G. Andersen, Michael Kaminsky

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Tags: Computer science, Operating systems

September 14, 2011 by hgpu

Optimizing a shared virtual memory system for a heterogeneous CPU-accelerator platform

Shoumeng Yan, Xiaocheng Zhou, Ying Gao, Hu Chen, Gansha Wu, Sai Luo, Bratin Saha

Tags: Computer science, Heterogeneous systems, Memory, Operating systems, Performance, Programming Languages

September 12, 2011 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Creating HW/SW co-designed MPSoPC’s from high level programming models

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

A shared file system abstraction for heterogeneous architectures

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Efficient Synchronization Primitives for GPUs

Operating Systems Challenges for GPU Resource Management

PTask: Operating System Abstractions To Manage GPUs as Compute Devices

Real-Time Handling of GPU Interrupts in LITMUSRT

Performing with CUDA

The case for VOS: the vector operating system

Optimizing a shared virtual memory system for a heterogeneous CPU-accelerator platform

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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