A hitchhiker's guide to CUDA programming
🎯GPU Kernels
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Moving past speculation: How deterministic CPUs deliver predictable AI performance
venturebeat.com·2d
🧠CPU Architecture
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flowengineR: A Modular and Extensible Framework for Fair and Reproducible Workflow Design in R
arxiv.org·3h
🔄ONNX
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Co-Simulation Framework for Parallel DNN Execution on Chiplet-Based Systems (UW–Madison, Washington State)
semiengineering.com·11h
🎯Tensor Cores
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eBPF Tutorial by Example: Monitoring GPU Driver Activity with Kernel Tracepoints
⏱️CUDA Events
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Why Multimodal AI Broke the Data Pipeline — And How Daft Is Beating Ray and Spark to Fix It
hackernoon.com·1d
🧮cuDNN
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Synopsys and NVIDIA Forge AI Powered Future for Chip Design and Multiphysics Simulation
semiwiki.com·18h
⏱️CUDA Events
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On the Structure of Floating-Point Noise in Batch-Invariant GPU Matrix Multiplication
arxiv.org·3h
✂️CUTLASS
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Evolving Ray and Kubernetes together for the future of distributed AI and ML
cloud.google.com·15h
🌐Distributed Computing
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Geonum – geometric number library for unlimited dimensions with O(1) complexity
✂️CUTLASS
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Don't let these 3 CPU specs trick you into paying more
xda-developers.com·12h
⚡Flash Attention
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Hydra: Dual Exponentiated Memory for Multivariate Time Series Analysis
arxiv.org·3h
📊Gradient Accumulation
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Uncrossed Multiflows and Applications to Disjoint Paths
arxiv.org·3h
📊CUDA Graphs
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PDE-SHARP: PDE Solver Hybrids Through Analysis & Refinement Passes
arxiv.org·3h
✂️CUTLASS
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