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Predicting the Execution Time of a kernel on a specific GPU using PTX code

Monika Dagar, Jorge Roldan

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 1650, nVidia GeForce GTX Titan XP, Performance, PTX, Tesla K20, Tesla K80, Tesla M60, Tesla P100, Tesla T4, Tesla V100

October 22, 2023 by hgpu

Auto-SpMV: Automated Optimizing SpMV Kernels on GPU

Mina Ashoury, Mohammad Loni, Farshad Khunjush, Masoud Daneshtalab

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Tags: Computer science, CUDA, Energy efficiency, Linear Algebra, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 1650, Sparse matrix

February 26, 2023 by hgpu

SaLoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs

Seongyeon Park, Hajin Kim, Tanveer Ahmad, Nauman Ahmed, Zaid Al-Ars, H. Peter Hofstee, Youngsok Kim, Jinho Lee

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Tags: Bioinformatics, Biology, CUDA, Databases, nVidia, nVidia GeForce GTX 1650, nVidia GeForce RTX 3090, Sequence alignment, Smith-Waterman algorithm, String matching

January 29, 2023 by hgpu

High Performance Simulation for Scalable Multi-Agent Reinforcement Learning

Jordan Langham-Lopez, Sebastian M. Schmon, Patrick Cannon

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia GeForce GTX 1650, Performance

July 17, 2022 by hgpu

Data transfer optimizations for heterogeneous managed runtime systems

Florin-Gabriel Blanaru

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Tags: Computer science, CUDA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1650, nVidia Quadro GP100, OpenCL

March 27, 2022 by hgpu

Performance Optimisations for Heterogeneous Managed Runtime Systems

Michail Papadimitriou

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Tags: Computer science, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1650, OpenCL, Performance, Thesis

November 14, 2021 by hgpu

Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations

Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K Prasanna

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Tags: Computer science, Deep learning, nVidia, nVidia GeForce GTX 1650

October 10, 2021 by hgpu

Automatically Exploiting the Memory Hierarchy of GPUs through Just-in-Time Compilation

Michail Papadimitriou, Juan Fumero, Athanasios Stratikopoulos, Christos Kotselidis

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Tags: Benchmarking, Computer science, Java, nVidia, nVidia GeForce GTX 1650, OpenCL, Package

May 23, 2021 by hgpu

Multiple-Tasks on Multiple-Devices (MTMD): Exploiting Concurrency in Heterogeneous Managed Runtimes

Michail Papadimitriou, Eleni Markou, Juan Fumero, Athanasios Stratikopoulos, Florin Blanaru, Christos Kotselidis

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Tags: Computer science, Heterogeneous systems, Java, Machine learning, nVidia, nVidia GeForce GTX 1650, OpenCL

April 11, 2021 by hgpu

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

Donatella Granata, Angelo Palombo, Federico Santini, Umberto Amato

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Tags: Algorithms, Heterogeneous systems, nVidia, nVidia GeForce GTX 1650, OpenCL, Sensing, Signal processing

February 2, 2020 by hgpu

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

pp-template: Template for Performance-Portable code development, targeting HOST-DEVICE computer architectures

An approach to performance portability through generic programming

Redco: A Lightweight Tool to Automate Distributed Training

Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs

OpenRAND: Reproducible Random Number For Parallel Computations

OpenRAND: A Performance Portable, Reproducible Random Number Generation Library for Parallel Computations

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high performance computing on graphics processing units: hgpu.org

Predicting the Execution Time of a kernel on a specific GPU using PTX code

Auto-SpMV: Automated Optimizing SpMV Kernels on GPU

SaLoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs

High Performance Simulation for Scalable Multi-Agent Reinforcement Learning

Data transfer optimizations for heterogeneous managed runtime systems

Performance Optimisations for Heterogeneous Managed Runtime Systems

Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations

Automatically Exploiting the Memory Hierarchy of GPUs through Just-in-Time Compilation

Multiple-Tasks on Multiple-Devices (MTMD): Exploiting Concurrency in Heterogeneous Managed Runtimes

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

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Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

pp-template: Template for Performance-Portable code development, targeting HOST-DEVICE computer architectures

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