Alif Is Creating SoC Solutions for Machine Learning with Cadence and Arm
Alif Semiconductor is bridging the gap between standard microcontrollers and high-end GPU solutions. They’re providing scalable, integrated, and secure microprocessors and microcontrollers for low-power machine learning (ML) tasks. To design these complex SoCs, Alif is using Cadence’s state-of-the-art EDA tools as well as the Arm® Cortex® and Ethos processors.
While standard MCUs can address simple ML tasks like keyword spotting or failure detection, tasks like facial or speech recognition are much heavier and require hundreds of giga operations per second (GOPS). Standard MCUs can’t deliver that. Designers would have to jump to the GPU classes to achieve that kind of performance, but they’re too costly, too big, and consume too much power.
To read the full article, click here
Related Semiconductor IP
- USB 20Gbps Device Controller
- AGILEX 7 R-Tile Gen5 NVMe Host IP
- 100G PAM4 Serdes PHY - 14nm
- Bluetooth Low Energy Subsystem IP
- Multi-core capable 64-bit RISC-V CPU with vector extensions
Related Blogs
- SoC QoS gets help from machine learning
- Take your neural networks to the next level with Arm's Machine Learning Inference Advisor
- NetSpeed Leverages Machine Learning for Automotive IC End-to-End QoS Solutions
- Machine Learning And Design Into 2018 - A Quick Recap
Latest Blogs
- The Hidden Threat in Analog IC Migration: Why Electromigration rules can make or break your next tapeout
- MIPI CCI over I3C: Faster Camera Control for SoC Architects
- aTENNuate: Real-Time Audio Denoising
- From guesswork to guidance: Mastering processor co-design with Codasip Exploration Framework
- Enabling AI Innovation at The Far Edge