AI CHIP STARTUP PUTS INFERENCE CARDS ON THE TABLE

#News(Startup) [ via IoTForIndiaGroup ]

In the deep learning inferencing game, there are plenty of chipmakers, large and small, developing custom-built ASICs aimed at this application set. But one obscure company appears to have beat them to the punch.

Habana Labs, a fabless semiconductor startup, began sampling its purpose-built inference processor for select customers back in September 2018, coinciding with the company’s emergence from stealth mode. Eitan Medina, Habana’s Chief Business Officer, claims its HL-1000 chip is now “the industry’s highest performance inference processor.” It’s being offered to customers in a PCIe card that goes by name of Goya.

According to Habana’s internal testing, Goya can inference 15,012 images/second on the ResNet50 image recognition benchmark, which would certainly qualify it for the world record. And the results are being spit out with a latency of just 1.3ms, which is more than adequate for real-time interaction.

Nvidia finest AI chip, the V100 GPU, manages something over 3,247 images/second at 2.5ms latency (which drops to 1,548 images/second if it wants to match Goya’s self-reported 1.3ms latency). For FPGAs, the best results so far for ResNet-50 inferencing appears to be the Xilinx Alveo U250, which clocks in at 3,700 images/second. CPUs are further behind at 1,225 images/second, and that’s for a dual-socket Intel Xeon (Skylake) Platinum 8180 server. The upcoming Cascade Lake-SP Xeon, which will benefit from the addition of Vector Neural Network Instructions (VNNI), is expected to deliver about twice the inferencing throughput as its Skylake predecessor.

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