Google & UC Berkeley’s Data-Driven Offline Optimization Approach Significantly Boosts Hardware Accelerator Performance, Reduces Simulation Time by More Than 90% | Synced
A research team from Google Research and UC Berkeley proposes PRIME, an offline data-driven approach that can architect hardware accelerators without any form of simulations. Compared to state-of-t...
Source: Synced | AI Technology & Industry Review
A research team from Google Research and UC Berkeley proposes PRIME, an offline data-driven approach that can architect hardware accelerators without any form of simulations. Compared to state-of-the-art simulation-driven methods, PRIME achieves impressive performance improvements of up to 1.54× while reducing the total required simulation time by up to 99 percent.