all AI news
Splitwise improves GPU usage by splitting LLM inference phases
Jan. 4, 2024, 5:02 p.m. | Brenda Potts
Microsoft Research www.microsoft.com
Expanded LLM use creates new demands on cloud GPU capacity. Splitwise presents an efficient solution by separating the two essential phases of LLM inference, achieving higher throughput within a limited power budget.
The post Splitwise improves GPU usage by splitting LLM inference phases appeared first on Microsoft Research.
budget capacity cloud cloud gpu gpu inference llm microsoft microsoft research power research research blog solution usage
More from www.microsoft.com / Microsoft Research
Research Focus: Week of May 13, 2024
4 days, 21 hours ago |
www.microsoft.com
LLM profiling guides KV cache optimization
1 week, 4 days ago |
www.microsoft.com
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US