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AMD Launches vLLM-ATOM Plugin to Deeply Optimize the Inference Performance of Domestic Large Models

AMD released the vLLM-ATOM plugin, aiming to fully tap into hardware potential without changing the existing workflow, significantly accelerating the inference of mainstream large language models such as DeepSeek-R1 and Kimi-K2. vLLM is an open-source framework optimized for throughput and GPU memory utilization in high-concurrency scenarios, focusing on request scheduling and cache management. The ATOM plugin further enhances this capability.

16k 6 hours ago
AMD Launches vLLM-ATOM Plugin to Deeply Optimize the Inference Performance of Domestic Large Models

Accelerating Domestic Large Models: AMD Launches vLLM-ATOM Plugin to Significantly Improve Inference Efficiency

AMD launched the vLLM-ATOM plugin, optimizing large language model deployment on AMD hardware. It boosts inference performance for Chinese models like DeepSeek-R1 and Kimi-K2 without altering existing workflows. Tailored for Instinct GPUs, it leverages vLLM's high memory efficiency, enabling low-cost technical migration and smooth performance upgrades.....

21.7k 22 hours ago
Accelerating Domestic Large Models: AMD Launches vLLM-ATOM Plugin to Significantly Improve Inference Efficiency
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