high performance computing on graphics processing units: hgpu.org

Federico Simmross-Wattenberg, Manuel Rodriguez-Cayetano, Javier Royuela-del-Val, Elena Martin-Gonzalez, Elisa Moya-Saez, Marcos Martin-Fernandez, Carlos Alberola-Lopez

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Tags: Heterogeneous systems, Image processing, Medicine, OpenCL, Package

August 5, 2018 by hgpu

CRUM: Checkpoint-Restart Support for CUDA’s Unified Memory

Rohan Garg, Apoore Mohan, Michael Sullivan, Gene Cooperman

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Tesla P100

August 5, 2018 by hgpu

Elementary functions: towards automatically generated, efficient, and vectorizable implementations

Hugues De Lassus Saint-Genies

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Tags: Algorithms, Code generation, Computer science, Elementary functions, Performance, Thesis

July 28, 2018 by hgpu

Optimization of OpenCL applications on FPGA

Albert Navarro Torrento

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

July 28, 2018 by hgpu

Smoothed-Particle Hydrodynamics Models: Implementation Features on GPUs

Sergey Khrapov, Alexander Khoperskov

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Tags: Astrophysics, CUDA, hydrodynamics, nVidia, OpenMP, Tesla K20, Tesla K40, Tesla K80

July 28, 2018 by hgpu

gSMat: A Scalable Sparse Matrix-based Join for SPARQL Query Processing

Xiaowang Zhang, Mingyue Zhang, Peng Peng, Jiaming Song, Zhiyong Feng, Lei Zou

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Tags: Computer science, CUDA, Databases, nVidia, Sparse matrix, Tesla M40

July 28, 2018 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Parallax: Automatic Data-Parallel Training of Deep Neural Networks

Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs

Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs

GPU schedulers: how fair is fair enough?

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices

CRUM: Checkpoint-Restart Support for CUDA’s Unified Memory

Elementary functions: towards automatically generated, efficient, and vectorizable implementations

Optimization of OpenCL applications on FPGA

Smoothed-Particle Hydrodynamics Models: Implementation Features on GPUs

gSMat: A Scalable Sparse Matrix-based Join for SPARQL Query Processing

Recent source codes

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

INT v.s. FP: A framework to compare low-bit integer and float-point formats

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

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