D-Matrix AI Chip Promises Efficient Transformer Processing

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D-Matrix AI Chip Promises Efficient Transformer Processing
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This article was written by Cambrian-AI Analyst Alberto Romero and Karl D-Matrix was founded in 2019 by two veterans in the field of AI hardware, Sid Sheth and Sudeep Bhoja, who previously worked together at Inphi (Marvell) and Broadcom.

Startup combines Digital In-Memory Compute and chiplet implementations for data-center-grade inferencing.D-Matrix was founded in 2019 by two veterans in the field of AI hardware, Sid Sheth and Sudeep Bhoja, who previously worked together at Inphi and Broadcom. The company was born at a singular moment for the field of AI, just two years after the popular transformer architecture was invented by Google Brain scientists.

Focusing on large multimodal models is what differentiates the company from its competitors. Transformer-based models are usually trained on high-performance GPUs , but performing inferences is a power efficiency story, not just performance at any cost. D-Matrix has found an innovative solution with which they claim to achieve 10–30x the efficiency of the current hardware.

Nighthawk emerges from the novel combination of three technological pillars. First is digital in-memory compute . The efficiency barrier that existing hardware suffers is due to the costs and performance limits caused by moving data around to do the computations. D-Matrix has mixed the accuracy and predictability of digital hardware with super-efficient IMC to create what D-Matrix believes is the first DIMC architecture for inference at the data center.

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