This talk provides an overview of the read-after-write data consistent mechanism in the Alluxio system. Alluxio Core Maintainer and Presto Committer share their recent work on Alluxio and Apache Iceberg integration, as well as some recent work from the Presto community on Iceberg connector.
ALLUXIO DAY VIII 2021
December 14, 2021
This talk provides an overview of the read-after-write data consistent mechanism in the Alluxio system. Alluxio Core Maintainer and Presto Committer share their recent work on Alluxio and Apache Iceberg integration, as well as some recent work from the Presto community on Iceberg connector.
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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.