Right this moment, d-Matrix, a pacesetter in high-efficiency AI-compute and inference processors, introduced Jayhawk, an Open Area-Particular Structure (ODSA) Bunch of Wires (BoW) based mostly chiplet platform for power environment friendly die-die connectivity over natural substrates. Constructing on the again of the Nighthawk chiplet platform launched in 2021, the 2nd technology Jayhawk silicon platform additional builds the scale-out chiplet based mostly inference compute platform. d-Matrix clients shall be in a position to use the inference compute platforms to handle Generative AI functions and Giant Language Mannequin transformer functions with a 10-20X enchancment in efficiency. 

Giant transformer fashions are creating new calls for for AI inference on the similar time that reminiscence and power necessities are hitting bodily limits. d-Matrix gives one of many first Digital In-Reminiscence Compute (DIMC) based mostly inference compute platforms to come to market, reworking the economics of complicated transformers and Generative AI with a scalable platform constructed to deal with the immense knowledge and energy necessities of inference AI. Enhancing efficiency could make energy-hungry knowledge facilities extra environment friendly whereas decreasing latency for finish customers in AI functions.

“With the announcement of our 2nd generation chiplet platform, Jayhawk, and a track record of execution, we are establishing our leadership in the chiplet ecosystem,” stated Sid Sheth, CEO of d-Matrix. “The d-Matrix team has made great progress towards building the world’s first in-memory computing platform with a chiplet-based architecture targeted for power hungry and latency sensitive demands of generative AI.”

d-Matrix’s novel compute platform makes use of an ingenious mixture of an in-memory compute-based IC structure, subtle instruments that combine with main ANN fashions, and chiplets in a block grid formation to assist scalability and effectivity for demanding ML workloads. By utilizing a modular chiplet-based method, knowledge heart clients can refresh compute platforms on a a lot quicker cadence utilizing a pre-validated chiplet structure. To allow this, d-Matrix plans to construct chiplets based mostly on each BoW and UCIe based mostly interconnects to allow a really heterogeneous computing platform that may accommodate third social gathering chiplets.

“d-Matrix has moved quickly to seize the chiplet opportunity,  which should give them a first-mover advantage,” stated Karl Freund, Founder and Principal Analyst at Cambrian-AI Analysis. “Anyone looking to add an AI accelerator to their SoC design would do well to investigate this new approach for efficient AI.”

The Jayhawk chiplet platform options:

  • 3mm, 15mm, 25 mm hint lengths on natural substrate
  • 16 Gbps/wire excessive bandwidth throughput
  • 6-nm TSMC course of know-how
  • <0.5 pJ/bit power effectivity

Jayhawk is at present obtainable for demos and analysis. d-Matrix shall be showcasing the Jayhawk platform on the Chiplet Summit Jan 24-26 in San Jose, CA

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The Obsessed Guy
Hi, I'm The Obsessed Guy and I am passionate about artificial intelligence. I have spent years studying and working in the field, and I am fascinated by the potential of machine learning, deep learning, and natural language processing. I love exploring how these technologies are being used to solve real-world problems and am always eager to learn more. In my spare time, you can find me tinkering with neural networks and reading about the latest AI research.

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