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Telekine: Secure Computing with Cloud GPUs

Tyler Hunt, Zhipeng Jia, Vance Miller, Ariel Szekely, Yige Hu, Christopher J. Rossbach, Emmett Witchel

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Tags: AMD RX Vega 64, ATI, Cloud, Computer science, nVidia, OpenCL, Security

March 1, 2020 by hgpu

A Systematic Survey of General Sparse Matrix-Matrix Multiplication

Jianhua Gao, Weixing Ji, Zhaonian Tan, Yueyan Zhao

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 1080 Ti, Sparse matrix, survey

March 1, 2020 by hgpu

Performance Counters based Power Modeling of Mobile GPUs using Deep Learning

Nadjib Mammeri, Markus Neu, Sohan Lal, Ben Juurlink

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Tags: Computer science, Deep learning, Energy-efficient computing, Heterogeneous systems, Neural networks, OpenCL, OpenGL, SoC

February 23, 2020 by hgpu

Verified Instruction-Level Energy Consumption Measurement for NVIDIA GPUs

Yehia Arafa, Ammar ElWazir, Abdelrahman ElKanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed Badawy, Gopinath Chennupati, Stephan Eidenbenz, Nandakishore Santhi

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Tags: Computer science, CUDA, Energy-efficient computing, Measurement techniques, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX Titan V, nVidia GeForce GTX Titan X, nVidia Titan RTX, PTX

February 23, 2020 by hgpu

Let’s sort this out: GPGPU Verification of Radix Sort

Dré van Oorschot

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Tags: Algorithms, Computer science, Package, Sorting

February 23, 2020 by hgpu

From English To Foreign Languages: Transferring Pre-trained Language Models

Ke Tran

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Tags: Computer science, NLP, nVidia, Tesla V100

February 23, 2020 by hgpu

High-Performance High-Order Stencil Computation on FPGAs Using OpenCL

Hamid Reza Zohouri, Artur Podobas, Satoshi Matsuoka

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Tags: Computer science, FPGA, OpenCL, Stencil computation

February 23, 2020 by hgpu

The Deep Learning Compiler: A Comprehensive Survey

Mingzhen Li, Yi Liu, Xiaoyan Liu, Qingxiao Sun, Xin You, Hailong Yang, Zhongzhi Luan, Depei Qian

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Tags: Compilers, Computer science, Deep learning, Machine learning, Performance

February 16, 2020 by hgpu

EASYPAP: a Framework for Learning Parallel Programming

Alice Lasserre, Raymond Namyst, Pierre-André Wacrenier

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Tags: Algorithms, AVX, Computer science, Education, MPI, OpenCL, OpenMP, Package, Pthreads

February 16, 2020 by hgpu

ISM2: Optimizing Irregular-Shaped Matrix-Matrix Multiplication on GPUs

Cody Rivera, Jieyang Chen, Nan Xiong, Shuaiwen Leon Song, Dingwen Tao

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Tags: Algorithms, Computer science, CUDA, GEMM, Linear Algebra, Matrix multiplication, nVidia, Tesla K40, Tesla M40, Tesla P100

February 16, 2020 by hgpu

Task-based, GPU-accelerated and Robust Library for Solving Dense Nonsymmetric Eigenvalue Problems

Mirko Myllykoski, Carl Christian Kjelgaard Mikkelsen

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Tags: Computer science, CUDA, Mathematical Software, nVidia, Package, Tesla V100

February 16, 2020 by hgpu

Working With Incremental Spatial Data During Parallel (GPU) Computation

Robert Chisholm

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Tags: Agent-based modeling, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan V, Package, Thesis

February 9, 2020 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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high performance computing on graphics processing units: hgpu.org

Applications

A Systematic Survey of General Sparse Matrix-Matrix Multiplication

Performance Counters based Power Modeling of Mobile GPUs using Deep Learning

Verified Instruction-Level Energy Consumption Measurement for NVIDIA GPUs

Let’s sort this out: GPGPU Verification of Radix Sort

From English To Foreign Languages: Transferring Pre-trained Language Models

High-Performance High-Order Stencil Computation on FPGAs Using OpenCL

The Deep Learning Compiler: A Comprehensive Survey

EASYPAP: a Framework for Learning Parallel Programming

ISM2: Optimizing Irregular-Shaped Matrix-Matrix Multiplication on GPUs

Task-based, GPU-accelerated and Robust Library for Solving Dense Nonsymmetric Eigenvalue Problems

Working With Incremental Spatial Data During Parallel (GPU) Computation

Recent source codes

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

SYCL Container

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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