Applied Scientist, Machine Learning Accelerator - Annapurna Labs

Our team is involved with pre-silicon design verification for custom IP. A critical requirement of the verification flow is the requirement of legal and realistic stimulus of a custom Machine Learning Accelerator Chip. Content creation is built using formal methods that model legal behavior of the design and then solving the problem to create the specific assembly tests. The entire frame work for creating these custom tests is developed using a SMT solver and custom software code to guide the solution space into templated scenarios. This highly visible and innovative role requires the design of this solving framework and collaborating with design verification engineers, hardware architects and designers to ensure that interesting content can be created for the projects needs.

Develop an understanding for a custom machine learning instruction set architecture.

Model correctness of instruction streams using first order logic.

Create custom API's to allow control over scheduling and randomness.

Deploy algorithms to ensure concurrent code is safely constructed.

Create coverage metrics to ensure solution space coverage.

Use novel methods like machine learning to automate content creation.