A group of academics in the US has launched an open source language for chip design based around Python and optimised for machine learning techniques.
The group at the University of California (UCLA) in the US is launching PyGears as a new hardware description language. This is based on the idea of agile chip design based on reusable components and high-level Python constructs.
By adopting it in the VLSI Signal Processing course, the UCLA Samueli School of Engineering says it has started to build a community that observes hardware through software paradigms, with the goal of accelerating hardware design and verification, by using more agile and composable modules.
“Chip design is getting more complex, with increasing costs and longer development cycles,” said Dr Dejan Markovic, electrical and computer engineering professor at UCLA. “PyGears addresses these challenges by adopting a modular build of hardware out of reusable components, which are built by a community of like-minded contributors. This works very well for small and large engineering teams alike. Hardware design and verification is based on the Python environment, reducing the barriers between software and hardware domains. The vision is to enable software people to code hardware.”
“Software’s greatest limitation is the relatively slow rate of hardware evolution,” said Shahin Farshchi, partner at Lux Capital. “PyGears stands on the shoulders of giants to accelerate hardware design closer to the speed of ‘coding,’ which will lead to magical new use cases that will underpin market-defining products and companies.”
PyGears was created by Dr Bogdan Vukobratovic, Head of R&D at Anari AI to provide more agile development rather than focussing on low level optimization and control in the VHDL and Verilog design languages.
PyGears provides control of all aspects up to the lowest layers, making the process multiple times more efficient. He also emphasizes that building complex architectures requires systems with more agility in development.
“PyGears was born in an effort to capture all good practices that I found useful during my career in a tool that could dramatically speed up the hardware implementation of complex architectures, especially if they are related to AI paradigms,” said Vukobratovic. “It is a free and open-source project that should be a good start in creating the next generation chip design, but that goal requires all of us to contribute to and determine the direction of hardware development. Otherwise, the AI world will not be sustainable in the future.”
“The development of new hardware design tools can strongly benefit from open-source solutions. To get the hardware industry out of the Stone-Age and make it more agile, we need new concepts shaped by the community,” said Dr Boris Murmann, a professor at Stanford University.
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