Archive · 1 Oct 2025
AI Optimization: New Paths in Hardware and Software
Imagine making computers smarter!
This story is about making AI, like the smart assistants on your phone, work even better.
It’s not just about the fancy chips (hardware) inside the computer; it's also about the programs (software) that tell those chips what to do.
An engineer named Rajalakshmi helps make the hardware and software work together super efficiently.
She helps programs use the special features of new computer chips, so they can do AI tasks faster.
This is done by planning and testing before the chips are even built.
This teamwork makes AI programs run much better, like giving them a turbo boost!
AI optimization requires collaboration between hardware and software teams.
Optimization efforts started with simulators before hardware availability.
Key AI libraries like OpenBLAS and ONNX Runtime were optimized.
Continuous integration builds streamlined testing and integration workflows.
The approach is called "silicon-to-systems."
- Who
- Rajalakshmi Srinivasaraghavan, a software engineer, optimized AI libraries.
- What
- AI performance optimization, focusing on hardware and software integration.
- When
- The process started before hardware was available using simulators.
- Where
- The optimization efforts focused on the IBM POWER10 processor.
- Why
- To unlock the full potential of AI through collaboration between hardware and software.
- Key Figure
- Rajalakshmi Srinivasaraghavan
- Processor Mentioned
- IBM POWER10
- Core Concept
- Silicon-to-Systems
- Technology Used
- Matrix Math Assist (MMA)
- Focus
- AI workload acceleration