2 Repos
Awesome GitHub RepositoriesDynamic Kernel Optimization
Runtime generation of specialized GPU kernels to maximize performance without manual compilation.
Distinct from GPU Kernel Implementations: Focuses on the dynamic generation and optimization process rather than static kernel implementations.
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Awesome Dynamic Kernel Optimization GitHub Repositories
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- deepseek-ai/deepep
deepseek-ai/DeepEP
9,736Auf GitHub ansehenDeepEP is a distributed model accelerator and expert-parallel communication library designed to optimize the training and inference of large-scale neural networks. It provides specialized GPU communication kernels and a remote GPU memory interface to facilitate high-throughput data exchange between hardware nodes. The system utilizes dynamic kernel generation to compile optimized GPU kernels during execution, removing the need for separate installation compilation steps. It implements virtual-lane traffic isolation to prevent interference between different data streams and employs routing met
Dynamically generates specialized GPU kernels during execution to improve performance and eliminate manual compilation.
Cuda - dusty-nv/jetson-inference
dusty-nv/jetson-inference
8,734Auf GitHub ansehenjetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti
Uses heuristics to automatically select the most efficient GPU kernel implementation based on problem size.
C++caffecomputer-visiondeep-learning
