and take efficiency to the next level. The only AI processor with Integrated RDMA

Processors purpose-built to unlock Intel Corporation announces the acquisition of Habana Labs, an Israel-based developer of programmable deep learning accelerators for the data center. For inference, the bigger focus is on getting a quick answer to the query being posed to the model, thus the need to reduce latency. As such, Habana’s performance advantage claim may be short-lived.
That’s why we’re thrilled to have an AI team of Habana’s caliber with a proven track record of execution joining Intel. Total scenario power=100W Efficiency (images/sec/watt): 151 Latency: 1.3msec including drivers Hardware: Goya HL-100; CPU Xeon Gold [email protected] <> Habana's Goya Processor. © 2020 Habana Labs Ltd. All rights reserved. NVIDIA has proved itself to be an agile innovator and a formidable competitor, and with its well-established CUDA software ecosystem, it is unlikely to cede its dominant market position any time soon. In general, you want as high an accuracy as possible, but in some situations, you may want to lower accuracy for better performance or vice-versa.

Combination Advances Intel’s AI Strategy, Strengthens Portfolio of AI Accelerators for the Data Center, Habana Labs chairman Avigdor Willenz stands near a rack that incorporates Habana Labs' HLS-1 Gaudi artificial intelligence training system at Habana Labs' office in Caesarea, Israel. Our combined IP and expertise will deliver unmatched computing performance and efficiency for AI workloads in the data center.”.

and lower total cost of ownership. As we reported back in June, when Habana unveiled the chip, seven of the ports are used to connect Gaudis within a node, leaving three to link up to other servers. That’s where Gaudi’s generous supply of networking capacity comes in. Is there any information on actual performance numbers for these chips in TFLOPs or TOPs anywhere or anything from Hotchips?
endobj It can process 15,000 ResNet-50 images/second with 1.3-ms latency at a batch size of 10 while running at 100 W (more than 5x the number of images than competing platforms). Thumbnail. Facebook originated this OCP module design, and several chip providers (but not NVIDIA) plan to support it.

For more details, see the MLPerf industry-wide results and whitepaper. Habana was one of the first AI chip startups to make its silicon available to datacenter customers. Gaudi represents Habana’s second attempt to break into the AI market following the commercial launch of its Goya inference chips in Q4 2018. This can be managed through a software API, which modifies the data type accordingly based on the desired accuracy.

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