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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

SkyFlow: Heterogeneous streaming for skyline computation using FlowGraph and SYCL

Jose Carlos Romero, Angeles Navarro, Andres Rodrıguez, Rafael Asenjo

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Tags: Computer science, Heterogeneous systems, Intel, Intel UHD 630, OpenMP, SYCL

December 4, 2022 by hgpu

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Manuel Costanzo, Enzo Rucci, Carlos García Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, Heterogeneous systems, Intel, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, OpenCL, Sequence alignment, SYCL, Tesla V100

November 27, 2022 by hgpu

Accelerating Encrypted Computing on Intel GPUs

Yujia Zhai, Mohannad Ibrahim, Yiqin Qiu, Fabian Boemer, Zizhong Chen, Alexey Titov, Alexander Lyashevsky

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Tags: Algorithms, Computer science, Deep learning, Intel, Package, Security, SYCL

October 3, 2021 by hgpu

Performance Portability and Evaluation of Heterogeneous Components of SeisSol Targeted to Upcoming Intel HPC GPUs

Ludwig Kratzl

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Intel, Intel UHD 630, MPI, nVidia, nVidia GeForce RTX 3090, OpenCL, Package, performance portability, SYCL, Thesis

August 29, 2021 by hgpu

Comparison of HPC Architectures for Computing All-Pairs Shortest Paths. Intel Xeon Phi KNL vs NVIDIA Pascal

Manuel Costanzo, Enzo Rucci, Ulises Costi, Franco Chichizola, Marcelo Naiouf

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Tags: Algorithms, All-Pairs Distance, Computer science, CUDA, HPC, Intel, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan X, Package

May 23, 2021 by hgpu

Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Nuno Fachada, Agostinho C. Rosa

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Tags: Agent-based modeling, AMD, cpu, Intel, OpenCL, simulation

July 24, 2019 by fakenmc

Automated Testing of Graphics Shader Compilers

Alastair F. Donaldson, Hugues Evrard, Andrei Lascu, Paul Thomson

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Tags: AMD Radeon R9 Fury, ARM, ATI, ATI Radeon HD 7700, Compilers, Computer science, GLSL, Intel, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan X, OpenGL, Rendering, Security, Shaders, WebGL

September 21, 2017 by hgpu

Input Space Splitting for OpenCL

Simon Moll, Johannes Doerfert, Sebastian Hack

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Tags: Compilers, Computer science, Intel, LLVM, OpenCL

March 5, 2016 by hgpu

A Survey of Architectural Techniques For Improving Cache Power Efficiency

Sparsh Mittal

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Tags: Architecture, cache, cpu, Energy-efficient computing, GPU, Intel, Memory, Power-efficient computing

January 19, 2015 by sparsh0mittal

Preliminary Experiments with XKaapi on Intel Xeon Phi Coprocessor

Joao Vicente Ferreira Lima, Francois Broquedis, Thierry Gautier, Bruno Raffin

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Tags: Computer science, Factorization, Intel, Intel Phi, Intel Xeon Phi

November 11, 2013 by hgpu

Understanding the Costs of Many-Task Computing Workloads on Intel Xeon Phi Coprocessors

Jeffrey Johnson, Scott J. Krieder, Benjamin Grimmer, Justin M. Wozniaky, Michael Wildeyz, Ioan Raicu

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Tags: Computer science, Heterogeneous systems, Intel, Intel Phi

October 21, 2013 by hgpu

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Evaluation of Rust for GPGPU high performance computing

Evaluation of Rust for GPGPU high-performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

Optimization of massive data applications on heterogeneous architectures

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Pulsar search acceleration using FPGAs and OpenCL templates

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

Fast Merge Tree Computation via SYCL

pocl: Portable Computing Language

Efficient OpenCL system integration of non-blocking FPGA accelerators

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

Python Suite for Advanced General Ensemble Simulations

PySAGES: flexible, advanced sampling methods accelerated with GPUs

GPU load-balancing library for regular and irregular computations

A Programming Model for GPU Load Balancing

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimization of massive data applications on heterogeneous architectures

SkyFlow: Heterogeneous streaming for skyline computation using FlowGraph and SYCL

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Accelerating Encrypted Computing on Intel GPUs

Performance Portability and Evaluation of Heterogeneous Components of SeisSol Targeted to Upcoming Intel HPC GPUs

Comparison of HPC Architectures for Computing All-Pairs Shortest Paths. Intel Xeon Phi KNL vs NVIDIA Pascal

Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Automated Testing of Graphics Shader Compilers

Input Space Splitting for OpenCL

A Survey of Architectural Techniques For Improving Cache Power Efficiency

Preliminary Experiments with XKaapi on Intel Xeon Phi Coprocessor

Understanding the Costs of Many-Task Computing Workloads on Intel Xeon Phi Coprocessors

Recent source codes

Evaluation of Rust for GPGPU high performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

pocl: Portable Computing Language

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

Python Suite for Advanced General Ensemble Simulations

GPU load-balancing library for regular and irregular computations

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