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An unsupervised parallel genetic cluster algorithm for graphics processing units

D. Hendricks, D. Cieslakiewicz, D. Wilcox, T. Gebbie

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Tags: Clustering, Computational finance, CUDA, Genetic programming, nVidia, nVidia GeForce 560 Ti, nVidia GeForce 660 Ti, nVidia GeForce GTX 660 M

March 23, 2014 by hgpu

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice

HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments

BAT: A standardized benchmark suite for auto-tuners

BAT: A Benchmark suite for AutoTuners

The Darmstadt Automotive Parallel HeterogeNEous (DAPHNE) Benchmark-Suite

Programming Heterogeneous Systems with General and Domain-Specific Frameworks

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

iGUARD: In-GPU Advanced Race Detection

iGUARD: In-GPU Advanced Race Detection

TaPaSCo: The Task Parallel System Composer

Optimizing a Hardware Network Stack to Realize an In-Network ML Inference Application

Tapenade Automatic Differentiation Engine

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

Colossal-AI: an integrated large-scale model training system with efficient parallelization techniques

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training

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