Neurealm conducted comprehensive power-performance-accuracy (PPA) benchmarking of state-of-the-art deep learning models on next-generation AI accelerator devices for a North America–based AI hardware company, producing detailed metrics that inform product positioning and future design choices.

Business Context

An AI hardware accelerator chip company needed transparent, accurate benchmarking data to evaluate key performance indicators—latency, throughput, accuracy, and power consumption—across multiple deep learning workloads. With new SDKs, evolving APIs, and varied board bring-up challenges, the client sought expertise to compare their silicon against established standards and derive actionable insights for marketing and future hardware specification planning.

Solutions

Neurealm’s team quickly mastered the new SDKs and carrier boards, ported standard state-of-the-art models into the proprietary formats, and developed inference scripts. They measured latency, throughput, and power under real DL workloads, calculated accuracy versus original frameworks, and delivered a transparent PPA analysis report that helped the customer position their AI hardware effectively and plan next-generation specification targets.