The opportunity
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
What you'll do
Translate high level architecture spec to micro-architecture feature requirements
Bring up new features in the performance/power model
Perform comprehensive PPA trade-offs for new architectural features
Extract insights for new features and micro-architecture power efficiency
Profile workloads, identify bottlenecks and project competition performance for benchmarking
Engage with SW teams for end-end application level modeling at cluster level
What they're looking for
- Identify kernel level HW acceleration level opportunities
- Masters/PhD in Electrical/Computer Engineering
- + years of experience across performance analysis and modeling across GPUs, CPUs or accelerator products
- Strong background in computer architecture and key high level architectural trade-offs
