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以o1 为起点,由于模型推理能力的增强,以及软件公司用 LLM 开发新产品或进行自我改造的积极性提升,推理需求指数级增长让今年下半年以来 CSP ASIC 显著受益,CSP 离下游需要推理的客户群体更近,Amazon、Google、微软等大厂都在通过自有芯片研减少对 GPU 的依赖。 2025 年 Inference 作为硬件板块的核心命题不会改变,考虑...
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👏微软亚洲研究院在NeurIPS ENSLP 2024获最佳论文奖!在NeurIPS 2024 ENSLP workshop这个专注于模型效率提升的研讨会上,微软亚洲研究院名为《Retrieval Attention: Accelerating Long-Context LLM Inference via Vector Retrieval》的论文荣获最佳论文奖(Best Paper Award)。该研究创造性地提出使用向量索引来动态检索最关键...
PyTorch (🥇55 · ⭐ 87K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 GitHub (👨💻 5.4K · 🔀 23K · 📥 76K · 📦 650K · 📋 50K - 31% open · ⏱️ 20.02.2025): git clone https://github.com/pytorch/pytorch PyPi (📥 40...
Cytoscape is a great fit for midsize datasets. However, for projects requiring high scalability or GPU-accelerated performance, alternatives like react-force-graph may be better suited. 8. Cosmograph (Embedded Tool) Image courtesy of Cosmograph ...
The default value is 0.90 and means that 90% of the free GPU memory will be used to save tokens in the KV cache. Based on that value, TensorRT-LLM can determine the maximum number of tokens in the KV cache manager. When both parameters are set, the maximum number of tokens in the ...
AirLLM: AirLLM optimizes inference memory usage, allowing 70B large language models to run inference on a single 4GB GPU card without quantization, distillation and pruning. And you can run 405B Llama3.1 on 8GB vram now. LLMHub: LLMHub is a lightweight management platform designed to streamli...
Introducing New KV Cache Reuse Optimizations in NVIDIA TensorRT-LLM Language models generate text by predicting the next token, given all the previous tokens including the input text tokens. Key and value elements of the... 7 MIN READ Jan 15, 2025 GPU Memory Essentials for AI Performance...