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Awesome GitHub RepositoriesClient Concurrency Analysis
Evaluating service latency and performance under varying levels of simultaneous client connections.
Distinct from Concurrent Latency Testing: Focuses on analyzing server-side performance under load, distinct from measuring network point latency.
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Awesome Client Concurrency Analysis GitHub Repositories
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- modeltc/lightllm
ModelTC/LightLLM
3,901在 GitHub 上查看LightLLM is a high-performance serving framework for deploying and executing large language models. It functions as a multi-GPU inference engine and server capable of handling dense architectures, mixture-of-experts designs, and multimodal models that process both text and images. The system is distinguished by its specialized support for Mixture-of-Experts models using expert parallelism and fused kernels. It implements structured text generation through deterministic state machines and pushdown automata to enforce precise output formats. To optimize throughput, the framework employs specula
Implements tools to test service performance and latency percentiles under simulated concurrent client loads.
Pythondeep-learninggptllama
