high performance computing on graphics processing units: hgpu.org

Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica

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Tags: ARM, Compilers, Computer science, CUDA, Deep learning, Neural networks, nVidia, Optimization, Search strategies, Tesla V100

June 21, 2020 by hgpu

The Rodinia Benchmark Suite in SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, Heterogeneous systems, OpenCL, Package, SYCL

June 14, 2020 by hgpu

AutoMat – Automatic Differentiation for Generalized Standard Materials on GPUs

Johannes Blühdorn, Nicolas R. Gauger, Matthias Kabel

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Tags: Computer science, CUDA, FFT, Mathematical Software, nVidia, nVidia Quadro GV100

June 14, 2020 by hgpu

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

Jiajian Xiao, Philipp Andelfinger, Wentong Cai, Paul Richmond, Alois Knoll, David Eckhoff

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Tags: Code generation, Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 2080 Ti, OpenCL, Package

June 7, 2020 by hgpu

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BLOCKBENCH: A Framework for Analyzing Private Blockchains

Blockchain Goes Green? Part II: Characterizing the Performance and Cost of Blockchains on the Cloud and at the Edge

hls4ml: Machine learning on FPGAs using HLS

Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

GPJSON: GPU-based JSON data processing system accessible via all GraalVM languages

GPU-based JSON data processing using structural indexes

NEPTUNE: Network- and GPU-aware management of serverless functions at the edge

NEPTUNE: Network- and GPU-aware Management of Serverless Functions at the Edge

HeCBench: a collection of Heterogeneous Computing benchmarks written with CUDA, HIP, SYCL (DPC++), and OpenMP-4.5

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

WARPSPEED: An analytic Data Volume and Performance Estimator for GPU Kernels

Analytical Performance Estimation during Code Generation on Modern GPUs

Celerity HLA: A high-level API on top of Celerity to support functional, C++20 range-adaptors-like patterns

The Celerity High-level API: C++20 for Accelerator Clusters

GPU-Sched

CASE: A Compiler-Assisted SchEduling Framework for Multi-GPU Systems

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

GPU-based matrix-free finite element solver exploiting symmetry of elemental matrices

Sparse GPU Kernels for Deep Learning

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

Automatic Kernel Generation for Volta Tensor Cores

Autotuning for Automatic Parallelization on Heterogeneous Systems

FPGA Based Satisfiability Checking

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

Ansor: Generating High-Performance Tensor Programs for Deep Learning

The Rodinia Benchmark Suite in SYCL

AutoMat – Automatic Differentiation for Generalized Standard Materials on GPUs

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

Recent source codes

BLOCKBENCH: A Framework for Analyzing Private Blockchains

hls4ml: Machine learning on FPGAs using HLS

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

GPJSON: GPU-based JSON data processing system accessible via all GraalVM languages

NEPTUNE: Network- and GPU-aware management of serverless functions at the edge

HeCBench: a collection of Heterogeneous Computing benchmarks written with CUDA, HIP, SYCL (DPC++), and OpenMP-4.5

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

WARPSPEED: An analytic Data Volume and Performance Estimator for GPU Kernels

Celerity HLA: A high-level API on top of Celerity to support functional, C++20 range-adaptors-like patterns

GPU-Sched

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