high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

CoreTSAR: Task Scheduling for Accelerator-aware Runtimes

Thomas R. W. Scogland, Wu-chun Feng, Barry Rountree, Bronis R. de Supinski

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C2070

November 22, 2012 by hgpu

Automatic generation of software pipelines for heterogeneous parallel systems

Jacques A. Pienaar, Srimat Chakradhar, Anand Raghunathan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C1060

November 22, 2012 by hgpu

ValuePack: value-based scheduling framework for CPU-GPU clusters

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

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Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Tesla C2050

November 21, 2012 by hgpu

Pattern Recognition with OpenCL Heterogeneous Platform

Jordan Vrtanoski, Toni Draganov Stojanovski

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, Neural networks, OpenCL, Pattern recognition

November 21, 2012 by hgpu

Accelerating MapReduce on a coupled CPU-GPU architecture

Linchuan Chen, Xin Huo, Gagan Agrawal

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Tags: APU, ATI, ATI Radeon HD 6550, Computer science, Data mining, Heterogeneous systems, Machine learning, MapReduce, OpenCL

November 20, 2012 by hgpu

High locality and increased intra-node parallelism for solving finite element models on GPUs by novel element-by-element implementation

Imre Kiss, Zsolt Badics, Szabolcs Gyimothy, Jozsef Pavo

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Tags: Computer science, CUDA, FEM, Finite element method, Heterogeneous systems, nVidia, nVidia GeForce GTX 590

November 18, 2012 by hgpu

Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Mayank Daga, Mark Nutter

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Tags: APU, ATI, ATI Radeon HD 7660, ATI Radeon HD 7970, Computer science, Databases, Heterogeneous systems, OpenCL

November 18, 2012 by hgpu

Parallel implementations of the MinMin heterogeneous computing scheduler in GPU

Mauro Canabe, Sergio Nesmachnow

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C1060

November 16, 2012 by hgpu

CUDA and OpenCL Implementations of 3D CT Reconstruction for Biomedical Imaging

Saoni Mukherjee, Nicholas Moore, James Brock, Miriam Leeser

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Tags: ATI, ATI Radeon HD 5870, Computed tomography, CT, CUDA, Heterogeneous systems, Image reconstruction, Medicine, nVidia, OpenCL, Tesla C2070

November 16, 2012 by hgpu

Device specialization in heterogeneous multi-GPU environments

Gabriele Cocco, Antonio Cisternino

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Tags: AMD Fusion, ATI, ATI IL, ATI Radeon HD 5870, Computer science, GPU cluster, Heterogeneous systems, Task scheduling

November 15, 2012 by hgpu

Reusable OpenCL FPGA Infrastructure

Stephen Alexander Chin

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, Thesis

November 8, 2012 by hgpu

Kite: Braided Parallelism for Heterogeneous Systems

J. Garrett Morris, Benedict R. Gaster, Lee Howes

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Tags: Compilers, Computer science, Heterogeneous systems, OpenCL, Programming techniques

November 5, 2012 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

CoreTSAR: Task Scheduling for Accelerator-aware Runtimes

Automatic generation of software pipelines for heterogeneous parallel systems

Pattern Recognition with OpenCL Heterogeneous Platform

Accelerating MapReduce on a coupled CPU-GPU architecture

High locality and increased intra-node parallelism for solving finite element models on GPUs by novel element-by-element implementation

Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Parallel implementations of the MinMin heterogeneous computing scheduler in GPU

CUDA and OpenCL Implementations of 3D CT Reconstruction for Biomedical Imaging

Device specialization in heterogeneous multi-GPU environments

Reusable OpenCL FPGA Infrastructure

Kite: Braided Parallelism for Heterogeneous Systems

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

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