面向大语言模型的高吞吐、低显存推理与服务引擎,通过 PagedAttention 等优化显著提升并发吞吐并降低显存占用,适合部署在线推理服务。
把 NumPy 风格的 Python 代码自动微分、向量化并 JIT 编译到 GPU/TPU,写起来像 NumPy,跑起来像高性能计算。
把分散在多家云上的 GPU 资源统一调度成一台「AI 超算」,自动选最便宜的可用算力跑训练、微调和推理任务,省去手动比价与跨云管理。
跨平台高性能推理与训练加速引擎,可直接加载 ONNX 模型,兼容 PyTorch、TensorFlow 等框架导出,解决模型在不同硬件上高效部署的问题。
一本面向大模型工程实践的开源手册,系统讲解 GPU 训练、推理、调试、网络与扩展性等落地问题,帮工程师把模型真正跑起来。
….com/basetenlabs/truss/pull/2730 feat(truss): Add TPU accelerator groundwork by @Sanjan611 in https://github.com/basetenlabs/truss/pull/2719 Full Changelog : https://gith
….com/basetenlabs/truss/pull/2730 feat(truss): Add TPU accelerator groundwork by @Sanjan611 in https://github.com/basetenlabs/truss/pull/2719 Full Changelog : https://gith
…ow reads from env $COLUMNS before falling back to tput — 556: - --date iso support — 27e0ce5 + test for 540: - Adds a simple Makefile Fixes - Fix crash on git dates witho
…on fixes for the still-experimental, undocumented TPU/XLA training path (tracked under issue 1058) — see Notable Changes below. No breaking changes in this release. ✨ Spo
…codeproject/CodeProject.AI-Server/pull/97 Use new TPU segment option by @seth-planet in https://github.com/codeproject/CodeProject.AI-Server/pull/99 Bugfix: incorrect sta
…//github.com/ultralytics/yolov5/pull/5699), [Edge TPU](https://github.com/ultralytics/yolov5/pull/3630) and [OpenVINO](https://github.com/ultralytics/yolov5/pull/6057) su