AI BriefingAccelerating BLOOMZ Inference on Gaudi2
Key point
Introduces how to efficiently deploy and run inference on the 176B-scale BLOOMZ model using 🤗 Optimum Habana on Habana Gaudi2 accelerators.
Details
The BLOOMZ model, with 176B parameters, requires about 352GB of memory at 16-bit precision, making it very challenging to deploy on a single device.
Habana Gaudi2 provides an environment capable of accommodating such large-scale models through a server configuration containing 8 HPUs (Habana Processing Units) with 96GB of memory each. Gaudi2 maximizes LLM training and inference performance through an architecture optimized for parallel computation.
Key technical features are as follows:
- Optimum Habana: Connects Gaudi2 with the 🤗 Transformers library to simplify model deployment.
- SynapseAI™ SDK: Optimizes execution through operator fusion, data layout management, and parallelization.
- DeepSpeed integration: Supports model and pipeline parallelism, efficiently distributing large-scale models across multiple devices.
Benchmark results show that Gaudi2 delivers superior performance in large-scale model inference compared to Nvidia A100 80GB.
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