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Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Amrita Mathuriya, Thorsten Kurth, Vivek Rane, Mustafa Mustafa, Lei Shao, Debbie Bard, Prabhat, Victor W Lee

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Tags: Benchmarking, Computer science, Deep learning, Intel Xeon Phi, Neural networks, Performance, TensorFlow

January 6, 2018 by hgpu

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Xinying Wang

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Tags: Computer science, Data mining, Factorization, FPGA, Intel Xeon Phi, Matrix decomposition, Semantic indexing, Signal processing, Text mining, Thesis

December 28, 2017 by hgpu

Design and Implementation of the Futhark Programming Language

Troels Henriksen

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Tags: AMD FirePro W8100, ATI, Computer science, Haskell, High-level Languages, nVidia, OpenCL, Package, Tesla K40, Thesis

December 28, 2017 by hgpu

A Generic Inverted Index Framework for Similarity Search on the GPU

Jingbo Zhou, Qi Guo, H. V. Jagadish, Lubos Krcal, Siyuan Liu, Wenhao Luan, Anthony K. H. Tung, Yueji Yang, Yuxin Zheng

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Tags: Computer science, CUDA, Hashing, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, OpenMPI, Package

December 28, 2017 by hgpu

A Survey of FPGA Based Neural Network Accelerator

Kaiyuan Guo, Shulin Zeng, Jincheng Yu, Yu Wang, Huazhong Yang

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Tags: Computer science, Computer vision, FPGA, Machine learning, Neural networks

December 28, 2017 by hgpu

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Waqar Ali, Heechul Yun

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Tags: Computer science, CUDA, nVidia, nVidia Jetson TK1, Operating systems, Performance, Security, SoC

December 28, 2017 by hgpu

Pass a Pointer: Exploring Shared Virtual Memory Abstractions in OpenCL Tools for FPGAs

Felix Winterstein, George Constantinides

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

December 24, 2017 by hgpu

Extending OmpSs for OpenCL kernel co-execution in heterogeneous systems

B. Perez, E. Stafford, J. L. Bosque, R. Beivide, S. Mateo, X. Teruel, X. Martorell, E. Ayguade

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, OmpSs, OpenCL, OpenMP, Tesla K20

December 24, 2017 by hgpu

An MPI-Based Python Framework for Distributed Training with Keras

Dustin Anderson, Jean-Roch Vlimant, Maria Spiropulu

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Tags: Computer science, CUDA, Deep learning, Keras, Machine learning, MPI, Neural networks, nVidia, nVidia GeForce GTX 1080, Package, Python, Tesla K80

December 24, 2017 by hgpu

An In-depth Performance Characterization of CPU- and GPU-based DNN Training on Modern Architectures

Ammar Ahmad Awan, Hari Subramoni, Dhabaleswar K. Panda

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Tags: Benchmarking, Caffe, Computer science, CUBLAS, CUDA, Deep learning, Intel Xeon Phi, Machine learning, nVidia, Tela K40, Tesla K80, Tesla P100

December 24, 2017 by hgpu

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

Lukas Polok

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Tags: Algorithms, Computer science, Differential equations, Factorization, FEM, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 680, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla K40, Thesis

December 19, 2017 by hgpu

OpenCL-accelerated Point Feature Histogram and Its Application in Railway Track Point Cloud Data Processing

Dongxu Lv, Peijun Wang, Wentao Li, Peng Chen

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Tags: Algorithms, AMD Radeon R7 260, ATI, Computer science, OpenCL

December 19, 2017 by hgpu

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Design and Implementation of the Futhark Programming Language

A Generic Inverted Index Framework for Similarity Search on the GPU

A Survey of FPGA Based Neural Network Accelerator

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Pass a Pointer: Exploring Shared Virtual Memory Abstractions in OpenCL Tools for FPGAs

Extending OmpSs for OpenCL kernel co-execution in heterogeneous systems

An MPI-Based Python Framework for Distributed Training with Keras

An In-depth Performance Characterization of CPU- and GPU-based DNN Training on Modern Architectures

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

OpenCL-accelerated Point Feature Histogram and Its Application in Railway Track Point Cloud Data Processing

Recent source codes

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

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