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Optimization of massive data applications on heterogeneous architectures

José Carlos Romero Moreno

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Tags: Computer science, FPGA, Heterogeneous systems, Intel, Intel UHD 630, OpenCL, Package, SYCL, Thesis

February 5, 2023 by hgpu

Efficient OpenCL system integration of non-blocking FPGA accelerators

Topi Leppänen, Atro Lotvonen, Panagiotis Mousouliotis, Joonas Multanen, Georgios Keramidas, Pekka Jääskeläinen

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

January 22, 2023 by hgpu

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks

Kun Wu, Mert Hidayetoğlu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-mei Hwu

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce RTX 3090

January 22, 2023 by hgpu

Distributed Calculations with Algorithmic Skeletons for Heterogeneous Computing Environments

Nina Herrmann, Herbert Kuchen

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeFroce RTX 2080 Ti, nVidia Quadro K620

January 15, 2023 by hgpu

OpenMP Advisor

Alok Mishra, Abid M. Malik, Meifeng Lin, Barbara Chapman

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Tags: AMD Radeon Instinct Mi50, ATI, Benchmarking, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, OpenMP, Tesla A100, Tesla K80, Tesla V100

January 15, 2023 by hgpu

A Domain-Extensible Compiler with Controllable Automation of Optimisations

Thomas Kœhler

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Tags: Code generation, Computer science, DSL, Heterogeneous systems, Image processing, Machine learning, OpenCL, Package, Thesis

January 8, 2023 by hgpu

Arax: a runtime framework for decoupling applications from heterogeneous accelerators

Manos Pavlidakis, Stelios Mavridis, Antony Chazapis, Giorgos Vasiliadis, Angelos Bilas

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce RTX 2080, OpenCL, Package

January 8, 2023 by hgpu

Extending MAGMA Portability with OneAPI

Anna Fortenberry, Stanimire Tomov

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce RTX 3060, oneAPI, Package, performance portability

December 25, 2022 by hgpu

mu-grind: A Framework for Dynamically Instrumenting HLS-Generated RTL

Parmida Vahdatniya, Amirali Sharifian, Reza Hojabr, Arrvindh Shriraman

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, Package, Scala

December 25, 2022 by hgpu

A Framework to Generate High-Performance Time-stepped Agent-based Simulations on Heterogeneous Hardware

Jiajian Xiao

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Tags: Computer science, FPGA, Heterogeneous systems, nVidia GeForce GTX 1060, nVidia GeForce RTX 2080 Ti, OpenCL, Thesis

December 19, 2022 by hgpu

FLIA: Architecture of Collaborated Mobile GPU and FPGA Heterogeneous Computing

Nan Hu, Chao Wang, Xuehai Zhou

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL

December 19, 2022 by hgpu

Assessing Application Efficiency and Performance Portability in Single-Source Programming for Heterogeneous Parallel Systems

August Ernstsson, Dalvan Griebler, Christoph Kessler

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, OpenMP, Package, performance portability, Tesla K20

December 11, 2022 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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high performance computing on graphics processing units: hgpu.org

Optimization of massive data applications on heterogeneous architectures

Efficient OpenCL system integration of non-blocking FPGA accelerators

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks

Distributed Calculations with Algorithmic Skeletons for Heterogeneous Computing Environments

OpenMP Advisor

A Domain-Extensible Compiler with Controllable Automation of Optimisations

Arax: a runtime framework for decoupling applications from heterogeneous accelerators

Extending MAGMA Portability with OneAPI

mu-grind: A Framework for Dynamically Instrumenting HLS-Generated RTL

A Framework to Generate High-Performance Time-stepped Agent-based Simulations on Heterogeneous Hardware

FLIA: Architecture of Collaborated Mobile GPU and FPGA Heterogeneous Computing

Assessing Application Efficiency and Performance Portability in Single-Source Programming for Heterogeneous Parallel Systems

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Most viewed papers (last 30 days)