optimize-for-gpu

SKILLWorkflowcommunauté
v0.0.0K-Dense-AIMITMis à jour il y a 5 jSource →

GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, c

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il y a 5 jDernière mise à jour
Skill
AuteurK-Dense-AI
Version0.0.0
LicenceMIT
CatégorieWorkflow
Formatsskill.md
PromptOuvrir (voir l’onglet Prompt)
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À propos

GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-tran

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