Machine learning software innovator Mipsology today announced that its Zebra AI inference accelerator achieved the highest efficiency based on the latest MLPerf inference benchmarking. Zebra on a Xilinx Alveo U250 accelerator card achieved more than 2x higher peak performance efficiency compared to all other commercial accelerators.
“We are very proud that our architecture proved to be the most efficient for computing neural networks out of all the existing solutions tested, and in ML Perf’s ‘closed’ category which has the highest requirements,” said Ludovic Larzul, CEO and founder, Mipsology. “We beat behemoths like NVIDIA, Google, AWS, and Alibaba, and extremely well-funded startups like Groq, without having to design a specific chip and by tapping the power of FPGA reprogrammable logic. Perhaps the industry needs to stop over-relying on only increasing peak TOPS. What is the point of huge, expensive silicon with 400+ TOPS if nobody can use the majority of it?”
