NVIDIA is not exactly known for their commitment to open source projects, but to be fair things have improved since Linus Torvalds gave them the finger a few years ago, although they don’t seem to help much with Nouveau drivers, I’ve usually read positive feedback for Linux for their Nvidia Jetson boards.
So this morning I was quite surprised to read the company had launched NVDLA (NVIDIA Deep Learning Accelerator), “free and open architecture that promotes a standard way to design deep learning inference accelerators”
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The project is based on Xavier hardware architecture designed for automotive products, is scalable from small to large systems, and is said to be a complete solution with Verilog and C-model for the chip, Linux drivers, test suites, kernel- and user-mode software, and software development tools all available on Github’s NVDLA account. The project is not released under a standard open source license like MIT, BSD or GPL, but instead NVIDIA’s own Open NVDLA license.
This an on-going project, and NVIDIA has a roadmap until H1 2018, at which point we should get FPGA support for accelerating software development, as well as support for TensorRT and other supported frameworks.
Via Phoronix
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Jean-Luc started CNX Software in 2010 as a part-time endeavor, before quitting his job as a software engineering manager, and starting to write daily news, and reviews full time later in 2011.
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