As part of our goal to evaluate benchmarks for AI & machine learning tasks in general and LLMs in particular, today we’ll be sharing results from llama.cpp‘s built-in benchmark tool across a number of GPUs wi
9xx5-013:基于官方发布的 MLPerf™ Inference v4.1 Llama2-70B-99.9 性能测试得分结果,包括服务器场景和离线场景下的结果(以“token/秒”为单位),这些结果于 2024 年 9 月 1 日检索自 https://mlcommons.org/benchmarks/inference-datacenter/ 中的以下条目:4.1-0070(预览)和 4.1.0022。MLPerf™ 名称和...
OpenSSL or compression speed, redis/static web server cases, geekbench and passmark etc) on 2000+ cloud server types atsparecores.com, and currently working on a new set of benchmarks to be run on all servers for LLM inference speed using tiny, medium-sized and larger...
除此之外,我们需要根据 Micro-benchmark 获取的计算及访存指令延迟数据,合理的排布访存指令和计算指令以达到相互掩盖延迟,实现软流水获得最优的吞吐。可见算子优化是一种平衡之道,在有限的资源中,探寻一种最优的平衡,访存指令与计算指令的平衡,寄存器占用与计算密度的平衡等等,为了实现这种微妙的平衡,准确的 Micro-benc...
8. All You Need Is One GPU: Inference Benchmark for Stable Diffusion https://lambdalabs.com/blog/inference-benchmark-stable-diffusion 9. Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture … https://arxiv.org/abs/2402.07033
Unlock Insights With High-Performance LLM Inference In the ever-evolving landscape of AI, businesses rely on LLMs to address a diverse range of inference needs. An AI inference accelerator must deliver the highest throughput at the lowest TCO when deployed at scale for a massive user base. ...
KV cache is used for autoregressive decoding in LLMs. It stores key-value pairs in multi-headed attention during the pre-filling phase of inference. During the decoding stage, new KV pairs get appended to the memory. KV cache stores the intermediate key and value ac...
可以先使用torch.nn.export函数将模型转换成onnx格式，然后就可以放到TensorRT框架上inference了。
One aspect of LLM inference that currently limits efficient use of resources is that it has two distinct phases with different characteristics: the prompt phase and the token-generation phase. During the prompt phase, LLMs process all user input, or prompts, in parallel, efficiently utilizing GPU...
Higher performance OpenAI LLM service than vLLM serve: A pure C++ high-performance OpenAI LLM service implemented with GPRS+TensorRT-LLM+Tokenizers.cpp, supporting chat and function call, AI agents, distributed multi-GPU inference, multimodal capabilitie