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Array-Oriented Languages and Polyhedral Compilation

Justin Paston-Cooper

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Tags: Computer science, High-level Languages, nVidia, nVidia GeForce RTX 2080, Thesis

September 6, 2020 by hgpu

GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks

Guyue Huang, Guohao Dai, Yu Wang, Huazhong Yang

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 2080, Package, Sparse matrix

July 12, 2020 by hgpu

Studies on CUDA Offloading for Real-Time Simulation and Visualization

Edgar Josafat Martinez-Noriega

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 970 M, nVidia GeForce RTX 2080, nVidia Jetson K1, Rendering, Thesis, Virtualization, Visualization

July 5, 2020 by hgpu

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

Szilárd Páll, Artem Zhmurov, Paul Bauer, Mark Abraham, Magnus Lundborg, Alan Gray, Berk Hess, Erik Lindahl

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Tags: Algorithms, AMD Radeon Instinct Mi50, AMD Vega FE, ATI, Chemistry, CUDA, Heterogeneous systems, Molecular dynamics, MPI, nVidia, nVidia GeForce RTX 2080, nVidia Quadro P 6000, OpenCL, Package, Tesla V100

June 21, 2020 by hgpu

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

Tsung-Wei Huang, Dian-Lun Lin, Yibo Lin, Chun-Xun Lin

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, Package, Performance

April 26, 2020 by hgpu

MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

Ji Liu, Abdullah-Al Kafi, Xipeng Shen, Huiyang Zhou

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Tags: Compilers, Computer science, FPGA, nVidia, nVidia GeForce RTX 2080, OpenCL, Performance

February 9, 2020 by hgpu

Interoperable GPU Kernels as Latency Improver for MEC

Juuso Haavisto, Jukka Riekki

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Tags: Computer science, GLSL, Graphics, nVidia, nVidia GeForce RTX 2080, nVidia Jetson TX2, Package, Vulkan

February 2, 2020 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

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high performance computing on graphics processing units: hgpu.org

Array-Oriented Languages and Polyhedral Compilation

GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks

Studies on CUDA Offloading for Real-Time Simulation and Visualization

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

Interoperable GPU Kernels as Latency Improver for MEC

Recent source codes

CLUEstering: a high-performance density-based clustering library for scientific computing

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