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Yulun Wang

Chronological feed of everything captured from Yulun Wang.

paper / yulunwang / Apr 9

NCCLX: Scaling Collective Communication for Large Language Models

The NCCLX framework addresses the communication bottlenecks for LLM training and inference on GPU clusters exceeding 100,000 GPUs. It optimizes for both high-throughput synchronous training and low-latency inference demands. This solution facilitates operation of next-generation LLMs at unprecedented scales.

collective-communicationdistributed-systemsgpu-clusterslarge-language-modelsllm-infrastructurehigh-performance-computingnetworking
“Traditional communication methods limit large language model (LLM) scaling due to throughput and latency issues.”