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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

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña

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Tags: Benchmarking, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, OpenACC, Package, PTX, Tesla K40, Tesla K80, Tesla V100

February 5, 2023 by hgpu

Pulsar search acceleration using FPGAs and OpenCL templates

Julian Oppermann, Mitchell B. Mickaliger, Oliver Sinnen

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Tags: Astrophysics, Design space exploration, FPGA, OpenCL, Package, Physics, Signal processing

January 29, 2023 by hgpu

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Manuel de Castro, Roberto R. Osorio, David L. Vilariño, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: Computer science, FPGA, OpenCL, Package

January 29, 2023 by hgpu

Fast Merge Tree Computation via SYCL

Arnur Nigmetov, Dmitriy Morozov

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Tags: Computational Geometry, Computer science, nVidia, nVidia GeForce RTX 2080 Ti, OpenMP, Package, SYCL

January 29, 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

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

Jinfan Chen, Shigang Li, Ran Gun, Jinhui Yuan, Torsten Hoefler

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Tags: Computer science, CUDA, Deep learning, Distributed computing, nVidia, nVidia A100, Package, Tesla P100

January 22, 2023 by hgpu

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Pablo F. Zubieta Rico, Ludwig Schneider, Gustavo Perez-Lemus, Riccardo Alessandri, Siva Dasetty, Cintia A. Menéndez, Yiheng Wu, Yezhi Jin, Trung Nguyen, John Parker, Andrew L. Ferguson, Juan J. de Pablo

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Tags: Biology, Chemistry, Computational Physics, CUDA, Molecular dynamics, nVidia, Package, Physics, Python, Tesla V100

January 22, 2023 by hgpu

A Programming Model for GPU Load Balancing

Muhammad Osama, Serban D. Porumbescu, John D. Owens

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Tags: Algorithms, Computer science, CUDA, load balancing, nVidia, Package, 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

Cramming: Training a Language Model on a Single GPU in One Day

Jonas Geiping, Tom Goldstein

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Tags: Computer science, Deep learning, NLP, nVidia, nVidia GeForce RTX 2080 Ti, nVidia RTX A4000, nVidia RTX A6000, Package

January 8, 2023 by hgpu

oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation

Jianhui Li, Zhennan Qin, Yijie Mei, Jingze Cui, Yunfei Song, Ciyong Chen, Yifei Zhang, Longsheng Du, Xianhang Cheng, Baihui Jin, Jason Ye, Eric Lin, Dan Lavery

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Tags: Code generation, Compilers, Computer science, Deep learning, OpenCL, Package

January 8, 2023 by hgpu

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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