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A performance/cost evaluation for a GPU-based drug discovery application on volunteer computing

Gines David Guerrero Hernandez, Baldomero Imbernon, Horacio Perez-Sanchez, Francisco Sanz, Jose M. Garcia, Jose M. Cecilia

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Tags: Bioinformatics, Biology, CUDA, Medicine, nVidia, nVidia GeForce 7300 GT, nVidia GeForce GTX 465, nVidia GeForce GTX 480, nVidia GeForce GTX 590, Tesla C2070, Tesla K20

May 21, 2014 by hgpu

Tabu Search on GPU

Adam Janiak, Wladyslaw A. Janiak, Maciej Lichtenstein

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Tags: Algorithms, Computer science, DirectX, HLSL, nVidia, nVidia GeForce 7300 GT, nVidia GeForce 8600 GT, Search

December 23, 2010 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

Agentic Code Optimization via Compiler-LLM Cooperation

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