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hgpu.org » Go

Deep Learning with GO

Derek L. Stinson
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May 17, 2020 by hgpu

The BondMachine toolkit: Enabling Machine Learning on FPGA

Mirko Mariotti, Loriano Storchi, Daniele Spiga, Davide Salomoni, Tommaso Boccali, Daniele Bonacorsi
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December 8, 2019 by hgpu

Recent source codes

sycl-bench: SYCL Benchmark Suite

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BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages
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Deep Learning with GO
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Task-Based Parallel Strategies for CFD Application in Heterogeneous CPU/GPU Resources

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DALI: a library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications

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Importance of Data Loading Pipeline in Training Deep Neural Networks
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DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

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86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy
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Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of the HPCChallenge Benchmark Suite
GEVO: GPU Code Optimization using Evolutionary Computation

GEVO: GPU Code Optimization using Evolutionary Computation

GEVO: GPU Code Optimization using Evolutionary Computation
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