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Porting a sparse linear algebra math library to Intel GPUs

Yuhsiang M. Tsai, Terry Cojean, Hartwig Anzt

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Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, HIP, Linear Algebra, nVidia, Package, Performance, Sparse, Sparse matrix, Tesla V100

March 21, 2021 by hgpu

GPGPU Task Scheduling Technique for Reducing the Performance Deviation of Multiple GPGPU Tasks in RPC-Based GPU Virtualization Environments

Jihun Kang, Heonchang Yu

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Tags: AMD Radeon RX 570, ATI, Cloud, Computer science, HPC, OpenCL, Task scheduling, Virtualization

March 21, 2021 by hgpu

Design, Implementation and Test of Efficient GPU to GPU Communication Methods

Stepan Vanecek

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Tags: AMD Radeon Instinct Mi50, ATI, Computer science, Heterogeneous systems, HIP, MPI, nVidia DGX-1, Thesis

January 3, 2021 by hgpu

Evaluating the Performance and Portability of Contemporary SYCL Implementations

Beau Johnston, Jeffrey S. Vetter, Josh Milthorpe

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Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, CUDA, Heterogeneous systems, HIP, Matrix multiplication, nVidia, OpenCL, Package, Performance, Tesla P100

November 29, 2020 by hgpu

Towards Co-execution on Commodity Heterogeneous Systems: Optimizations for Time-Constrained Scenarios

Raúl Nozal, Jose Luis Bosque, Ramon Beivide

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Tags: AMD Radeon R7, ATI, Computer science, Heterogeneous systems, load balancing, nVidia, nVidia GeForce GTX 950, OpenCL, Package, performance portability, Task scheduling

November 1, 2020 by hgpu

Transparent Acceleration of Java-based Deep Learning Engines

Athanasios Stratikopoulos, Mihai-Cristian Olteanu, Ian Vaughan, Zoran Sevarac, Nikos Foutris, Juan Fumero, Christos Kotselidis

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Tags: AMD RX Vega 64, ATI, Computer science, Computer vision, Deep learning, Java, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

October 4, 2020 by hgpu

Performance portability through machine learning guided kernel selection in SYCL libraries

John Lawson

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Tags: AMD R9 Nano, ATI, Auto-Tuning, Benchmarking, Clustering, Computer science, Machine learning, Package, Performance, performance portability, SYCL

September 6, 2020 by hgpu

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Alexander Brauckmann

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Tags: AMD Radeon HD 7970, ATI, Code generation, Computer science, LLVM, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 970, OpenCL, Thesis

July 12, 2020 by hgpu

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Hartwig Anzt, Terry Cojean, Goran Flegar, Fritz Göbel, Thomas Grützmacher, Pratik Nayak, Tobias Ribizel, Yuhsiang Mike Tsai, Enrique S. Quintana-Ortí

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Tags: Algorithms, AMD Radeon VII, ATI, Computer science, CUDA, HIP, Linear Algebra, Mathematical Software, nVidia, Package, Sparse, Sparse matrix, Tesla V100

July 5, 2020 by hgpu

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

Yuhsiang M. Tsai, Terry Cojean, Tobias Ribizel, Hartwig Anzt

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Tags: AMD Radeon VII, ATI, Computer science, CUDA, Linear Algebra, Mathematical Software, nVidia, Package

June 28, 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

Software Testing – Test Suite Compilation and Execution Optimizations

Panagiotis Stratis

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Tags: ATI, ATI Radeon HD 5450, Benchmarking, Computer science, Heterogeneous systems, Optimization, SYCL, Thesis

June 14, 2020 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

Porting a sparse linear algebra math library to Intel GPUs

Design, Implementation and Test of Efficient GPU to GPU Communication Methods

Evaluating the Performance and Portability of Contemporary SYCL Implementations

Towards Co-execution on Commodity Heterogeneous Systems: Optimizations for Time-Constrained Scenarios

Transparent Acceleration of Java-based Deep Learning Engines

Performance portability through machine learning guided kernel selection in SYCL libraries

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

Software Testing – Test Suite Compilation and Execution Optimizations

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

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