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Speeding up the evaluation of evolutionary learning systems using GPGPUs

Maria Franco, Natalio Krasnogor, Jaume Bacardit

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Tags: BioHEL, Evolutionary Computations, LCS, Learning Classifier System, Machine learning, Tesla C1060

November 1, 2012 by mariaux

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GPJSON: GPU-based JSON data processing system accessible via all GraalVM languages

GPU-based JSON data processing using structural indexes

NEPTUNE: Network- and GPU-aware management of serverless functions at the edge

NEPTUNE: Network- and GPU-aware Management of Serverless Functions at the Edge

HeCBench: a collection of Heterogeneous Computing benchmarks written with CUDA, HIP, SYCL (DPC++), and OpenMP-4.5

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

WARPSPEED: An analytic Data Volume and Performance Estimator for GPU Kernels

Analytical Performance Estimation during Code Generation on Modern GPUs

Celerity HLA: A high-level API on top of Celerity to support functional, C++20 range-adaptors-like patterns

The Celerity High-level API: C++20 for Accelerator Clusters

GPU-Sched

CASE: A Compiler-Assisted SchEduling Framework for Multi-GPU Systems

Efficient Execution of OpenMP on GPUs

Efficient Execution of OpenMP on GPUs

Explicit Caching HYB based SpMV

Explicit caching HYB: a new high-performance SpMV framework on GPGPU

matrix_inversion algorithm

Performance study on GPU offloading techniques using the Gauss matrix inverse algorithm

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