Attendees can join us at Intel’s booth #A105 to gain useful insights from Intel and Habana experts and architects on how to optimize deep learning performance and lower the total cost of ownership. We’ll show off the inference of large-scale workloads on two state-of-the-art large language models—the 12 billion parameter Dolly 2.0 and 176 billion parameter BLOOM (Big Science Language Open-science Open-access Multilingual) models. We'll also show Intel Gaudi 2 processor near-linear scaling of training capacity on the Stable Diffusion* model from one to 64 processors.
BLOOM is a 176-billion-parameter model trained to perform a variety language models such as question/answer, content generation, and text sequence completion. It can handle 46 different languages and 13 programming languages, and is slightly larger than GPT-3*. Designed and trained as part of the BigScience initiative, BLOOM is an open-science project that involves researchers and engineers from all over the world. Hugging Face*, a leading innovator in state-of-the-art AI software, provided this assessment of Intel Gaudi 2 processor on the BLOOM model.
Dolly 2.0 is a new 12B parameter model released in April that enables chat, multi-question/answer and other language functions. This model was crowdsourced from 13,000 behavioral demonstrations done by 5,000 Databricks employees, who spent several months creating a new dataset for commercial use. The initial dataset and model details are available under the Creative Commons License, allowing full access for any purpose.
Habana’s Jarek Dukat provides a closer look on scaling networking capacity with Intel Gaudi processor on the Voyager Supercomputer in the San Diego Supercomputer Center's workshop, "Experience with Building and Providing Novel AI-Focused Hardware for the Science and Engineering Community." The workshop will be conducted on Thursday, May 25, from 9:00 p.m. to 1:00 p.m. in Hall Y9 on the second floor.