high performance computing on graphics processing units: hgpu.org

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Large-Scale Compute-Intensive Analysis via a Combined In-Situ and Co-Scheduling Workflow Approach

Christopher Sewell, Katrin Heitmann, Hal Finkel, George Zagaris, Suzanne T. Parete-Koon, Patricia K. Fasel, Adrian Pope, Nicholas Frontiere, Li-ta Lo, Bronson Messer, Salman Habib, James Ahrens

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Tags: Computer science, GPU cluster, N-body simulation, nVidia, OpenCL, Task scheduling, Tesla K20

December 12, 2015 by hgpu

Accelerating Exact Similarity Search on CPU-GPU Systems

Takazumi Matsumoto, Man Lung Yiu

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Tags: Algorithms, ATI, Computer science, Data mining, Heterogeneous systems, Nearest neighbour, nVidia, nVidia GeForce GTX 780 Ti, OpenCL

December 12, 2015 by hgpu

GRATER: An Approximation Workflow for Exploiting Data-Level Parallelism in FPGA Acceleration

Atieh Lotfi, Abbas Rahimi, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Rajesh K. Gupta

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Code generation, Computer science, FPGA, OpenCL

December 12, 2015 by hgpu

Transforming C OpenMP Programs for Verification in CIVL

Michael Rogers

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Tags: Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Pthreads, Thesis

December 10, 2015 by hgpu

High Performance Histograms on SIMT and SIMD Architectures

M.E.R. Berger

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Tags: AMD Radeon R9 290X, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, nVidia GeForce GTX 660, nVidia GeForce GTX 750, OpenCL, Performance, Thesis

December 10, 2015 by hgpu

A Semi-Automated Tool Flow for Roofline Anaylsis of OpenCL Kernels on Accelerators

Servesh Muralidharan, Kenneth O'Brien, Christian Lalanne

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Tags: Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla K20

December 8, 2015 by hgpu

Towards Memory-Efficient Answering of Tree-Shaped SPARQL Queries using GPUs

Jedrzej Potoniec, Michal Madziar

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Source codes

Tags: Computer science, Data mining, Databases, OpenCL, Package

December 8, 2015 by hgpu

Scaling Deep Learning on Multiple In-Memory Processors

Lifan Xu, Dong Ping Zhang, Nuwan Jayasena

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Tags: ATI, ATI Radeon HD 7970, Computer science, Deep learning, Machine learning, OpenCL

December 8, 2015 by hgpu

An Accelerator based on the rho-VEX Processor: an Exploration using OpenCL

Hugo van der Wijst

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Tags: Computer science, FPGA, hardware acceleration, OpenCL, Thesis

December 4, 2015 by hgpu

Nested Parallelism on GPU: Exploring Parallelization Templates for Irregular Loops and Recursive Computations

Da Li, Hancheng Wu, Michela Becchi

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Tags: Computer science, nVidia, OpenCL, Tesla K20

December 4, 2015 by hgpu

Bridging OpenCL and CUDA: A Comparative Analysis and Translation

Junghyun Kim, Thanh Tuan Dao, Jaehoon Jung, Jinyoung Joo, Jaejin Lee

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL

December 1, 2015 by hgpu

A Problem-Based Learning Approach to GPU Computing

Robert Geist, Joshua A. Levine, James Westall

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX Titan X, OpenCL, Partial differential equations, PDEs

November 29, 2015 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

Large-Scale Compute-Intensive Analysis via a Combined In-Situ and Co-Scheduling Workflow Approach

Accelerating Exact Similarity Search on CPU-GPU Systems

GRATER: An Approximation Workflow for Exploiting Data-Level Parallelism in FPGA Acceleration

Transforming C OpenMP Programs for Verification in CIVL

High Performance Histograms on SIMT and SIMD Architectures

A Semi-Automated Tool Flow for Roofline Anaylsis of OpenCL Kernels on Accelerators

Towards Memory-Efficient Answering of Tree-Shaped SPARQL Queries using GPUs

Scaling Deep Learning on Multiple In-Memory Processors

An Accelerator based on the rho-VEX Processor: an Exploration using OpenCL

Nested Parallelism on GPU: Exploring Parallelization Templates for Irregular Loops and Recursive Computations

Bridging OpenCL and CUDA: A Comparative Analysis and Translation

A Problem-Based Learning Approach to GPU Computing

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

Most viewed papers (last 30 days)