AI BriefingStarCoder Inference Accelerated 7x on Intel Xeon
Key point
Through Optimum Intel and quantization techniques, StarCoder's inference performance on Intel Xeon processors was improved by more than 7x.
Details
Announced an optimization achievement that accelerates inference speed of the StarCoder-15B model by more than 7x on 4th Gen Intel Xeon processors.
The core optimization strategies are as follows:
- Quantization: Applied 8-bit (INT8) and 4-bit quantization to resolve memory bandwidth bottlenecks. It utilizes Weight Only Quantization (WOQ), which quantizes only the weights, and Static Quantization (SQ), which quantizes both weights and activation functions.
- Speculative Decoding: Integrated Assisted Generation technology to maximize inference efficiency.
- Hardware Acceleration: Utilized Intel® Advanced Matrix Extensions (AMX) of 4th Gen Xeon to accelerate BFloat16 and Int8 operations.
This technology is implemented through Hugging Face Optimum Intel and Intel Extension for PyTorch (IPEX), enabling more efficient deployment of code generation LLMs on Intel infrastructure.
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