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Ethos-N78 Boosts AI Efficiency

June 2, 2020

Author: Mike Demler

The new Ethos-N78 is Arm’s second-generation deep-learning accelerator (DLA), offering more performance and better efficiency than last year’s Ethos-N77. Both designs implement the same Scylla architecture, but the N78 boasts 40% greater DRAM-bandwidth efficiency. It supports up to twice as many multiply-accumulate (MAC) units as well, and design improvements enable them to run 25% faster. In this new high-end configuration, the N78 can deliver peak performance of 10 trillion operations per second (TOPS). It also gives designers more flexibility to optimize the accelerator for their application.

The intellectual-property (IP) vendor declined to share absolute performance measurements for popular neural networks but said that, using similar configurations, an N78 operating at the same clock frequency as its predecessor delivers an average of 25% more inferences per second. Arm attributes this gain to improvements in activation- and weight-compression. By reducing DRAM transactions and increasing the percentage of operations that run directly from on-chip SRAM, these changes improve area efficiency (inferences per second per square millimeter) by 25%.

Ethos-N78’s bandwidth improvements make it well suited to handling high-resolution images, so it’s a good candidate for 4K TVs and the next generation of 8K TVs, as well as surveillance cameras. Rather than engage in a meaningless race to provide the most TOPS, the company has wisely focused on increasing efficiency. Arm was late to the DLA market, but it’s gaining traction in consumer devices where Cortex CPUs and Mali GPUs are popular.

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