JAX on GPUs: Implementation Strategies for Enterprise Machine Learning
JAX is rapidly emerging as the framework of choice for teams who need both research flexibility and production performance. While PyTorch dominates the ML ...
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Introducing NVIDIA SHARP on Lambda 1CC: Next-Gen Performance for Distributed AI Workloads
Lambda’s 1-Click Clusters(1CC) provide AI teams with streamlined access to scalable, multi-node GPU clusters, cutting through the complexity of distributed infrastructure. Now, we're pushing the envelope further by integrating NVIDIA's Scalable Hierarchical Aggregation and Reduction Protocol (SHARP) into our multi-tenant 1CC environments. This technology reduces communication latency and improves bandwidth efficiency, directly accelerating training speed of distributed AI workloads.
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LLM performance up 15.4%: MLPerf v5.1 confirms NVIDIA HGX B200 on Lambda is built for enterprise inference
Inference at scale is still too slow. Large models often stall under real-world load, burning time, compute, and user trust. That’s the problem we set out to ...
Lambda and Cologix debut NVIDIA HGX B200 AI clusters in Columbus, Ohio
AI infrastructure is no longer confined to the coasts. With Lambda’s one-click clusters, Supermicro’s energy-efficient systems, and Cologix’s carrier-dense ...
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