high performance computing on graphics processing units: hgpu.org

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Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse Linear Algebra Computations

Yuhsiang Mike Tsai, Terry Cojean, Hartwig Anzt

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia A100, Performance, Sparse, Sparse matrix

August 23, 2020 by hgpu

Heterogeneous parallel computing for image registration and linear algebra applications

Orestis Zachariadis

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Tags: CUDA, Heterogeneous systems, Image processing, Image registration, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 1050, nVidia GeForce RTX 2070, Package, Sparse matrix, Thesis

August 9, 2020 by hgpu

Ignite-GPU: a GPU-enabled in-memory computing architecture on clusters

Amir Hossein Sojoodi, Majid Salimi Beni, Farshad Khunjush

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 680, Package

August 9, 2020 by hgpu

Parallel acceleration of CPU and GPU range queries over large data sets

Mitchell Nelson, Zachary Sorenson, Joseph M. Myre, Jason Sawin, David Chiu

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080

August 9, 2020 by hgpu

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

Aditya Agarwal, Yupeng Han, Maxim Likhachev

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1070, Package, Robotics, Tesla P100, Tesla V100

August 9, 2020 by hgpu

Bounds Checking on GPU

Troels Henriksen

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance

August 2, 2020 by hgpu

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

David J. Lusher, Satya P. Jammy, Neil D. Sandham

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Tags: cfd, Code generation, CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, Numerical simulation, nVidia, OpenCL, OpenMP, OpenMPI, Package, Python, Tesla P100

August 2, 2020 by hgpu

Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM

Zijing Gu

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Tags: Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, nVidia, Package, Sparse matrix, Tesla T4

August 2, 2020 by hgpu

Darknet on OpenCL: a multi-platform tool for object detection and classification

Piotr Sowa, Jacek Izydorczyk

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Tags: ARM, Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia Titan RTX, OpenCL, Package

July 26, 2020 by hgpu

Bit-level Parallelization of 3DES Encryption on GPU

Kaan Furkan Altınok, Afşin Peker, Alptekin Temizel

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1660, nVidia GeForce RTX 2060, Package, Security

July 26, 2020 by hgpu

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Yongbin Gu, Wenxuan Wu, Yunfan Li, Lizhong Chen

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 1080 Ti, Package, Performance

July 26, 2020 by hgpu

Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads

Gina Yuan, Shoumik Palkar, Deepak Narayanan, Matei Zaharia

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Python, Tesla P100

July 19, 2020 by hgpu

GPUODEBenchmarks: Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers

Automating Heterogeneous Parallelism in Numerical Differential Equations

Dat3M: Memory Model Aware Verification

Towards Unified Analysis of GPU Consistency

NVIDIA Federated Learning Application Runtime Environment

Supercharging Federated Learning with Flower and NVIDIA FLARE

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

PSCToolkit: solving sparse linear systems with a large number of GPUs

CATBench: Benchmarking Framework

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

General-purpose Polyhedral Compilers

A Survey of General-purpose Polyhedral Compilers

Optimal Kernel Orchestration for Tensor Programs with Korch

Astaroth: A Scalable Multi-GPU Library for Stencil Computations

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

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high performance computing on graphics processing units: hgpu.org

Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse Linear Algebra Computations

Heterogeneous parallel computing for image registration and linear algebra applications

Ignite-GPU: a GPU-enabled in-memory computing architecture on clusters

Parallel acceleration of CPU and GPU range queries over large data sets

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

Bounds Checking on GPU

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM

Darknet on OpenCL: a multi-platform tool for object detection and classification

Bit-level Parallelization of 3DES Encryption on GPU

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads

Recent source codes

GPUODEBenchmarks: Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers

Dat3M: Memory Model Aware Verification

NVIDIA Federated Learning Application Runtime Environment

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

PSCToolkit: solving sparse linear systems with a large number of GPUs

CATBench: Benchmarking Framework

General-purpose Polyhedral Compilers

Optimal Kernel Orchestration for Tensor Programs with Korch

Astaroth: A Scalable Multi-GPU Library for Stencil Computations

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking

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