Edge startup offers legacy support and ML acceleration

April 08, 2020 // By Peter Clarke
Edge startup offers legacy support and ML acceleration
Sima.ai is a 2018 inferencing chip startup developing MLSoC, a convolutional neural network platform aimed at computer vision while support legacy applications with an embedded ARM processor.

The company has a 16nm chip design in progress due to tape out at end of 2020. The company is aiming at processing the highest frames per second per watt. Machine-learning supported surveillance is one opportunity. The company claims that cycle-accurate simulations indicate MLSoC will be able to achieve 1000fps/watt for ResNet50 working with 224 by 224 frames from conventional image sensors.

The company claims this is 10x to 30x improvement over alternatives. The chip when it appears will offer performance from 50TOPS at 5W to 200TOPS at 20W and therefore offering 10TOPS/W.

Applications include: semi-autonomous and fully autonomous vehicles; untethered robots; secure diagnostics, secure computer vision

Kavitha Prasad, vice president of system solutions at Sima.ai, presented MLSoC at the Linley Spring Processor Conference on April 7 and opened by saying sima means 'edge' in Sanskrit.

The design is targeting 1GHz clock frequency in 16nm manufacturing process and includes up to four camera lines; a video pipeline including licensed image signal processor and computer vision processor cores; an ARM subsystem and LPDDR4 or LPDDR5 data connections out. Prasad the choice of DRAM interface is still under consideration. As is the ARM core. This will be either a CortexA6x or Cortex-A72 or Cortex-A75, Prasad said.

The MLSoC includes a security block that performs encryption and it also includes a safety block that enables designs that meet ISO 26262 and ASIL automotive standards. Am Arteris network-on-chip efficiently connects all these subsystems.

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