high performance computing on graphics processing units: hgpu.org

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Performance Monitoring of Multi-FPGA Systems

Arzhang Rafii

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Tags: Computer science, FPGA, Package, Performance, Thesis

April 11, 2021 by hgpu

Accelerating Deep Neural Networks implementation: A survey

Meriam Dhouibi, Ahmed Karim Ben Salem, Afef Saidi, Slim Ben Saoud

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Tags: ASIC, Computer science, Deep learning, FPGA, HLS, Neural networks, OpenCL, Optimization, Performance, survey

March 28, 2021 by hgpu

Accelerating Sparse Approximate Matrix Multiplication on GPUs

Xiaoyan Liu, Yi Liu, Ming Dun, Bohong Yin, Hailong Yang, Zhongzhi Luan, Depei Qian

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, Performance, Sparse matrix, Tesla V100

March 28, 2021 by hgpu

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

A Deep Learning Based Cost Model for Automatic Code Optimization

Riyadh Baghdadi, Massinissa Merouani, Mohamed-Hicham Leghettas, Kamel Abdous, Taha Arbaoui, Karima Benatchba, Saman Amarasinghe

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

March 21, 2021 by hgpu

Using hardware performance counters to speed up autotuning convergence on GPUs

Jiří Filipovič, Jana Hozzová, Amin Nezarat, Jaroslav Oľha, Filip Petrovič

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Tags: Auto-Tuning, Computer science, CUDA, HPC, Machine learning, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2080, OpenCL, Package, Performance, Vulkan

February 23, 2021 by hgpu

Computational Performance Predictions for Deep Neural Network Training: A Runtime-Based Approach

Geoffrey X. Yu, Yubo Gao, Pavel Golikov, Gennady Pekhimenko

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2070, Performance, Python, Tesla P100, Tesla V100

February 7, 2021 by hgpu

Why is FPGA-GPU Heterogeneity the Best Option for Embedded Deep Neural Networks?

Walther Carballo-Hernández, Maxime Pelcat, François Berry

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Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Neural networks, nVidia, nVidia Jetson TX2, Performance

February 7, 2021 by hgpu

Efficient MPI-based Communication for GPU-Accelerated Dask Applications

Aamir Shafi, Jahanzeb Maqbool Hashmi, Hari Subramoni, Dhabaleswar K. (DK) Panda

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Tags: Computer science, CUDA, Distributed computing, MPI, nVidia, Package, Performance, Python, Tesla V100

January 31, 2021 by hgpu

Interactive Parallelization of C Programs in SAPFOR

Nikita Kataev

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Tags: Computer science, CUDA, LLVM, nVidia, nVidia GeForce GTX 1660 Ti, OpenCL, Package, Performance

January 3, 2021 by hgpu

Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing

Xuewen Cui

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Tags: Artificial intelligence, Auto-Tuning, Computer science, CUDA, HPC, Machine learning, nVidia, OpenMP, Performance, Tesla K40, Tesla P100, Tesla V100, Thesis

December 20, 2020 by hgpu

Exploring FPGA Optimizations to Compute Sparse Numerical Linear Algebra Kernels

Federico Favaro, Ernesto Dufrechou, Pablo Ezzatti, Juan P. Oliver

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Tags: Computer science, FPGA, Linear Algebra, OpenCL, Optimization, Performance, Sparse

December 6, 2020 by hgpu

pharos: performance monitoring instrumentation for multi-FPGA systems

Performance Monitoring of Multi-FPGA Systems

Efficient Video Compression via Content-Adaptive Super-Resolution

CUDA Modular Polynomial (CUMODP) Library

Parallel Arbitrary-precision Integer Arithmetic

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

CUDA Tutorial - Cryptanalysis of Classical Ciphers Using Modern GPUs and CUDA

CUDA Tutorial – Cryptanalysis of Classical Ciphers Using Modern GPUs and CUDA

Ginkgo: a high-performance linear algebra library for manycore systems, with a focus on sparse solution of linear systems

Porting a sparse linear algebra math library to Intel GPUs

Exa.TrkX: Machine Learning for Particle Track Reconstruction

Physics and Computing Performance of the Exa.TrkX TrackML Pipeline

A Compiler Infrastructure for Accelerator Generators

LIKWID: A Lightweight Performance-Oriented Tool Suite

ECM modeling and performance tuning of SpMV and Lattice QCD on A64FX

hls4ml: A package for machine learning inference in FPGAs

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

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* * *

2021

April

27-29

Munich, Germany

9th International Workshop on OpenCL and SYCL, 2021

2020

December

10-14

Virtually in Barcelona, Spain

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

2020

November

24-27

Naha, Okinawa, Japan

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2021

January

13-15

Shenzhen, China

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

2020

December

14-16

Bangkok, Thailand

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020

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high performance computing on graphics processing units: hgpu.org

Performance Monitoring of Multi-FPGA Systems

Accelerating Deep Neural Networks implementation: A survey

Accelerating Sparse Approximate Matrix Multiplication on GPUs

Porting a sparse linear algebra math library to Intel GPUs

A Deep Learning Based Cost Model for Automatic Code Optimization

Using hardware performance counters to speed up autotuning convergence on GPUs

Computational Performance Predictions for Deep Neural Network Training: A Runtime-Based Approach

Why is FPGA-GPU Heterogeneity the Best Option for Embedded Deep Neural Networks?

Efficient MPI-based Communication for GPU-Accelerated Dask Applications

Interactive Parallelization of C Programs in SAPFOR

Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing

Exploring FPGA Optimizations to Compute Sparse Numerical Linear Algebra Kernels

Recent source codes

pharos: performance monitoring instrumentation for multi-FPGA systems

Efficient Video Compression via Content-Adaptive Super-Resolution

CUDA Modular Polynomial (CUMODP) Library

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

CUDA Tutorial - Cryptanalysis of Classical Ciphers Using Modern GPUs and CUDA

Ginkgo: a high-performance linear algebra library for manycore systems, with a focus on sparse solution of linear systems

Exa.TrkX: Machine Learning for Particle Track Reconstruction

A Compiler Infrastructure for Accelerator Generators

LIKWID: A Lightweight Performance-Oriented Tool Suite

hls4ml: A package for machine learning inference in FPGAs

Most viewed papers (last 30 days)

Featured events

9th International Workshop on OpenCL and SYCL, 2021

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020