GainSight — data lifetime profiling for heterogeneous on-chip memory
An open-source framework that extracts cycle-accurate data lifetimes from accelerator workloads and turns them into optimal heterogeneous on-chip memory compositions.
Projects
Three systems that between them cover the path I care about: measure what a workload actually does with memory, prove what the best placement for it is, and put the result on silicon.
Flan — solver-backed memory placement in MLIR
A compiler framework that formulates data placement across heterogeneous memory as an Optimization Modulo Theories problem and solves it with Z3, producing provably optimal placement schedules instead of hand-written heuristics.
GEMMA — 16nm AI accelerator tapeout
A 16nm gain-cell eDRAM AI accelerator I helped design and verify through the register-transfer level, including its embedded memory test logic and refresh controller, now fabricated as working silicon.
Coursework and academic projects are on the Academics page, and papers are on the Research page.