high performance computing on graphics processing units: hgpu.org

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Effective GPU Sharing Under Compiler Guidance

Chao Chen, Chris Porter, Santosh Pande

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Tags: Compilers, Computer science, CUDA, LLVM, Neural networks, nVidia, Tesla P100, Tesla V100

July 25, 2021 by hgpu

Face.evoLVe: A High-Performance Face Recognition Library

Qingzhong Wang, Pengfei Zhang, Haoyi Xiong, Jian Zhao

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Tags: AI, Computer science, Deep learning, Package, PyTorch

July 25, 2021 by hgpu

StreamBlocks: A compiler for heterogeneous dataflow computing

Endri Bezati, Mahyar Emami, Jörn Janneck, James Larus

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, OpenCL, Package, Performance

July 25, 2021 by hgpu

A method for decompilation of AMD GCN kernels to OpenCL

K.I. Mihajlenko, M.A. Lukin, A.S. Stankevich

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Tags: Compilers, Computer science, OpenCL, Package, Python

July 25, 2021 by hgpu

DNN is not all you need: Parallelizing Non-Neural ML Algorithms on Ultra-Low-Power IoT Processors

Enrico Tabanelli, Giuseppe Tagliavini, Luca Benini

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Tags: Computer science, FPGA, Machine learning, Neural networks, nVidia, Package, SoC, Tesla A100

July 25, 2021 by hgpu

Accelerating Regular-Expression Matching on FPGAs with High-Level Synthesis

Devon Callanan

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Tags: Computer science, FPGA, OpenCL, Security, Thesis

July 18, 2021 by hgpu

OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration

Daouda Diakite, Nicolas Gac, Maxime Martelli

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Tags: Computed tomography, Computer science, CT, FPGA, HLS, Medicine, OpenCL, Tomography

July 18, 2021 by hgpu

Designing a high-performance boundary element library with OpenCL and Numba

T. Betcke, M. W. Scroggs

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Tags: Computer science, HPC, nVidia, nVidia Quadro RTX 3000, OpenCL, Package, PyOpenCL, Python

July 18, 2021 by hgpu

Optimisation and GPU code generation of Stencils for Futhark

Christian Charlie Virt, Jonathan Wraa-Hansen

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, nVidia GeForce RTX 2080 Ti, OpenCL, Performance, Thesis

July 18, 2021 by hgpu

GPTPU: Accelerating Applications using Edge Tensor Processing Units

Kuan-Chieh Hsu, Hung-Wei Tseng

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Machine learning, Neural networks, nVidia, OpenCL, TPU

July 18, 2021 by hgpu

Bringing OpenCL to Commodity RISC-V CPUs

Tine Blaise, Seyong Lee, Jeff Vetter, Hyesoon Kim

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Tags: Benchmarking, Computer science, HPC, OpenCL, Package

July 11, 2021 by hgpu

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian Foster, Zhao Zhang

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia A100, nVidia DGX-A100, Package, Tesla V100

July 11, 2021 by hgpu

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Applications

Effective GPU Sharing Under Compiler Guidance

Face.evoLVe: A High-Performance Face Recognition Library

StreamBlocks: A compiler for heterogeneous dataflow computing

A method for decompilation of AMD GCN kernels to OpenCL

DNN is not all you need: Parallelizing Non-Neural ML Algorithms on Ultra-Low-Power IoT Processors

Accelerating Regular-Expression Matching on FPGAs with High-Level Synthesis

OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration

Designing a high-performance boundary element library with OpenCL and Numba

Optimisation and GPU code generation of Stencils for Futhark

GPTPU: Accelerating Applications using Edge Tensor Processing Units

Bringing OpenCL to Commodity RISC-V CPUs

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

Recent source codes

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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