This presentation will include information about how Alluxio and NetApp StorageGRID helps enterprises accelerate the adoption of cloud and optimize their resource spend on a modern hybrid big data architecture. The conversation will cover use case and architecture info from a variety of enterprises and some of the high level technical details of how these business solutions are constructed.
This presentation will include information about how Alluxio and NetApp StorageGRID helps enterprises accelerate the adoption of cloud and optimize their resource spend on a modern hybrid big data architecture. The conversation will cover use case and architecture info from a variety of enterprises and some of the high level technical details of how these business solutions are constructed.
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Videos
TorchTitan is a proof-of-concept for Large-scale LLM training using native PyTorch. It is a repo that showcases PyTorch's latest distributed training features in a clean, minimal codebase.
In this talk, Tianyu will share TorchTitan’s design and optimizations for the Llama 3.1 family of LLMs, spanning 8 billion to 405 billion parameters, and showcase its performance, composability, and scalability.
As large-scale machine learning becomes increasingly GPU-centric, modern high-performance hardware like NVMe storage and RDMA networks (InfiniBand or specialized NICs) are becoming more widespread. To fully leverage these resources, it’s crucial to build a balanced architecture that avoids GPU underutilization. In this talk, we will explore various strategies to address this challenge by effectively utilizing these advanced hardware components. Specifically, we will present experimental results from building a Kubernetes-native distributed caching layer, utilizing NVMe storage and high-speed RDMA networks to optimize data access for PyTorch training.