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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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RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

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FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

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PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

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CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

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UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

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CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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