Accelerating your AI deep learning model training with multiple GPU

Picture of Press Press Updated on July 19, 2022

Whitepapers
Accelerating your AI deep learning model training with multiple GPU

Deep Learning has shown remarkable results in many fields.Instant parameter adjustment is substantial for a successful deep learning model. To accelerate training process of deep learning, many studies are designed to use distributed deep learning systems with multiple GPUs.

Leave your contact information to download the whitepaper.
White Paper: GPU-Initiated, Liquid-Cooled, Ultra-High-Density Storage for Next-Gen AI

1 min read

White Paper: GPU-Initiated, Liquid-Cooled, Ultra-High-Density Storage for Next-Gen AI

This paper introduces a paradigm shift in storage architecture designed to overcome the CPU-centric data path bottlenecks in modern AI workloads. By...

Read More
White Paper: KV Cache Offload to Improve AI Inferencing Cost and Performance

1 min read

White Paper: KV Cache Offload to Improve AI Inferencing Cost and Performance

This paper explores a disaggregated key-value (KV) storage architecture designed to efficiently offload KV cache tensors for generative AI workloads.

Read More
Autonomous AI Agent for End-to-End Component Data Extraction

1 min read

Autonomous AI Agent for End-to-End Component Data Extraction

This paper explores an advanced framework designed to automate the extraction of important attributes from unstructured part datasheets. By...

Read More