IHWK and Microchip to launch new analog compute solution for edge AI/ML inferencing
AI solutions provider Intelligent Hardware Korea (IHWK) is developing a neuromorphic computing platform for neurotechnology devices and field programmable neuromorphic devices.
Partnering with Microchip Technology on the solution, IHWK will use the company’s silicon storage technology to develop the neuromorphic computing platform as Microchip Technology provides an evaluation system for its SuperFlash memBrain neuromorphic memory solution.
The company says the solution is based on Microchip’s nonvolatile memory (NVM) SuperFlash technology and is optimized to perform vector matrix multiplication (VMM) for neural networks through an analog in-memory compute approach.
With the aim of addressing the rapid rise of Artificial Intelligence (AI) computing at the edge of the network and its associated inferencing algorithms, the memBrain technology evaluation kit is designed to enable IHWK to demonstrate the power efficiency of its neuromorphic computing platform for running inferencing algorithms at the edge.
IHWK anticipates 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.
“By using proven NVM rather than alternative off-chip memory solutions to perform neural network computation and store weights, Microchip’s memBrain computing-in-memory technology is poised to eliminate the massive data communications bottlenecks otherwise associated with performing AI processing at the network’s edge,” says Mark Reiten, vice president of SST, Microchip’s licensing business unit.
Working 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.”
To develop the APU, IHWK says it is also working with Korea Advanced Institute of Science & Technology (KAIST), Daejeon, for device development and Yonsei University, Seoul, for device design assistance.
When completed, the APU is expected to optimize system-level algorithms for inferencing and operate between 20-80 TeraOPS per watt.
“Korea is an important hotspot for AI semiconductor development,” adds Sanghoon Yoon, IHWK branch manager.
“Our experts on nonvolatile and emerging memory have validated that Microchip’s memBrain product based on proven NVM technology is the best option when it comes to creating in-memory computing systems.”
IHWK is currently also leveraging SuperFlash memory’s floating gate cells’ nonvolatility in a bid to achieve a new benchmark in low-power edge computing devices supporting machine learning inference using advanced ML models.
Article Topics
AI/ML | edge computing | IHWK | Microchip Technology | network edge
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