{"id":783734,"date":"2023-09-13T09:00:18","date_gmt":"2023-09-13T13:00:18","guid":{"rendered":"https:\/\/www.marketnewsdesk.com\/index.php\/microchip-teams-up-with-intelligent-hardware-korea-ihwk-to-develop-an-analog-compute-platform-to-accelerate-edge-ai-ml-inferencing\/"},"modified":"2023-09-13T09:00:18","modified_gmt":"2023-09-13T13:00:18","slug":"microchip-teams-up-with-intelligent-hardware-korea-ihwk-to-develop-an-analog-compute-platform-to-accelerate-edge-ai-ml-inferencing","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/microchip-teams-up-with-intelligent-hardware-korea-ihwk-to-develop-an-analog-compute-platform-to-accelerate-edge-ai-ml-inferencing\/","title":{"rendered":"Microchip Teams Up with Intelligent Hardware Korea (IHWK) to Develop an Analog Compute Platform to Accelerate Edge AI\/ML Inferencing"},"content":{"rendered":"

\nUsing Microchip\u2019s memBrain\u2122 nonvolatile in-memory compute technology and working with universities, IHWK is creating a SoC processor for neurotechnology devices
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CHANDLER, Ariz., Sept. 13, 2023 (GLOBE NEWSWIRE) — To address the rapid rise of Artificial Intelligence (AI) computing at the edge of the network and its associated inferencing algorithms, Intelligent Hardware Korea (IHWK) is developing a neuromorphic computing platform for neurotechnology devices and field programmable neuromorphic devices. Microchip Technology (Nasdaq: MCHP)<\/strong>, via its Silicon Storage Technology (SST)<\/u><\/strong><\/a> subsidiary, is assisting with development of this platform by providing an evaluation system for its SuperFlash<\/u><\/strong>\u00ae<\/u><\/strong><\/sup> memBrain\u2122 neuromorphic memory solution<\/u><\/strong><\/a>. The solution is based on Microchip\u2019s industry-proven nonvolatile memory (NVM) SuperFlash technology and is optimized to perform vector matrix multiplication (VMM) for neural networks through an analog in-memory compute approach.<\/p>\n

The memBrain technology evaluation kit is designed to enable IHWK to demonstrate the absolute power efficiency of its neuromorphic computing platform for running inferencing algorithms at the edge. The end goal is to create an ultra-low-power analog processing unit (APU) for applications such as generative AI models, autonomous cars, medical diagnosis, voice processing, security\/surveillance and commercial drones.<\/p>\n

As current neural net models for edge inference may require 50 million or more synapses (weights) for processing, it becomes challenging to have enough bandwidth for the off-chip DRAM required by purely digital solutions, creating a bottleneck for neural net computing that throttles overall compute power. In contrast, the memBrain solution both stores synaptic weights in the on-chip floating gate in ultra-low-power sub-threshold mode and uses the same memory cells to perform the computations\u2014offering significant improvements in both power efficiency and system latency. When compared to traditional digital DSP and SRAM\/DRAM based approaches, it delivers 10 to 20 times lower power usage per inference decision and can significantly reduce the overall bill of materials.<\/p>\n

To develop the APU, IHWK is also working with Korea Advanced Institute of Science & Technology (KAIST), Daejeon, for device development and Yonsei University, Seoul, for device design assistance. The final APU is expected to optimize system-level algorithms for inferencing and operate between 20-80 TeraOPS per Watt, which is the best performance available for a computing-in-memory solution designed for use in battery-powered devices.<\/p>\n

\u201cBy using proven NVM rather than alternative off-chip memory solutions to perform neural network computation and store weights, Microchip\u2019s memBrain computing-in-memory technology is poised to eliminate the massive data communications bottlenecks otherwise associated with performing AI processing at the network\u2019s edge,\u201d said Mark Reiten, vice president of SST, Microchip\u2019s licensing business unit. \u201cWorking with IHWK, the universities and early adopter customers is a great opportunity to further prove our technology for neural processing and advance our involvement in the AI space by engaging with a leading R&D company in Korea.\u201d<\/p>\n

\u201cKorea is an important hotspot for AI semiconductor development,\u201d said Sanghoon Yoon, IHWK branch manager. \u201cOur experts on nonvolatile and emerging memory have validated that Microchip\u2019s memBrain product based on proven NVM technology is the best option when it comes to creating in-memory computing systems.\u201d<\/p>\n

Permanently storing neural models inside the memBrain solution\u2019s processing element also supports instant-on functionality for real-time neural network processing. IHWK is leveraging SuperFlash memory\u2019s floating gate cells\u2019 nonvolatility to achieve a new benchmark in low-power edge computing devices supporting machine learning inference using advanced ML models.<\/p>\n

For information contact info@sst.com<\/u><\/strong><\/a> or the appropriate regional contact listed on the SST website<\/u><\/strong><\/a>.<\/p>\n

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