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Not an ML topic, but still about hardware. Hardware security evaluation of MAX10 intel FPGA. Invasive and non-invasive attacks
Huawei released MindSpor, Tensorflow style AI computing framework, in August 2019.

Announced support of the following hardware platforms: Ascend 910, high performance AI processor for training, and Ascend 310, power efficient AI processor. Probably, it should also include support of Kirin990, Huawei SoC of mobile devices.

On the last week Huawei announced that Mindspor is open source now.
Eetimes podcast

KEVIN KREWELL: Well, to my mind, once again, the Linley Conference (April 6-9) got taken over by AI companies. And in this case, I think the primary highlights were the AI companies. We got to see a new company, Tens Turnt (?), come to light and talk about their solution. Grok finally really opened up the kimono and talked about the internal architecture of their chip. And they were a show, not a no-show this time. The small guys were making progress. The very low power guys like Gray Matter, they’re all moving forward with their products. And I think were a number of IP companies. Actually, interesting, Flex Logic, which has been an IP company for FPGAs, sort of pivoted a bit. So they’re still making their FPGA stuff, but they’re also building dedicated chips for AI using a DSP core they created that works well for machine learning applications. So they actually went ahead and built their own chip, and they’re showing some great promise in terms of performance.

It was a lot of interesting technologies. A lot of the IP guys like Seefa had some really good DSP. ARM talked a little more about their accelerator for MCUs for Ethos U55, which is their machine learning accelerator. Not new, but it’s a key product dealing with ARM, which is a key vendor.

And then something completely different now was the RISC-V guys talking about vector processing (?). That’s the next wave of architecture changes for the RISC-V guys. They’re getting into vector processing and tightly coupling it to the instruction set of RISC-V CPUs.
https://youtu.be/oxOvziuHHN0


The challenges of AI at the edge cannot merely be overcome by advances in AI software infrastructures. The solution lies in the critical rethinking of AI hardware at the edge, to achieve real-time processing with limited memory and the preservation of data privacy while not sacrificing the accuracy of the AI algorithms. Gain expert insights on this subject as Dr Sakya Dasgupta of Edgecortix Inc. shares his knowledge about edge computing and the challenges for enabling the future of AI at the edge. Date: 22 April 2020

Breaking Down Artificial Intelligence at the Edge by Dr Sakyasingha Dasgupta, Founder and CEO, Edgecortix, Inc.
Nanosemi (industry famous for PA linearization technology) announced availability of its NaNoTransformer technology. The technology operates at a mathematical level to augment mathematics of neural networks and generates implementations that provide higher accuracy or lower MACs. The output neural network can be targeted towards any platform such as CPU, GPU, FPGA or ASIC.
FCCM 2020
THE FUTURE OF FPGA-ACCELERATION IN
CLOUD AND DATA CENTERS

May 6th, 2020,
09:00 am - 03:00 pm PDT
Program
Zoom Event
Telegram group of VLSI chaps @vlsi_chaps - ASIC chip developers community

We will share updates, news, Jobs, quizzes, codes, topics, Conferences, papers, PDFs, books, class notes, materials, discussion, query solving, research trends, tool suggestions, tool helps, tool reviews or any other help in the field of VLSI.

VLSI Chaps
https://www.tg-me.com/vlsi_chaps
Book publisher Springer just released over 400 book titles that can be downloaded free of charge following the corona-virus outbreak.
Here’s fhe full overview

Among them 65 ML and DS books, read the list of selected books here
DRILLING DOWN INTO THE SIPEARL EUROPEAN ARM SERVER CHIP

The EU develops it's own server processor, both for general purposes and exascale computing. Matrix math and FPGA accelerators also coming from European suppliers.

Initiative is driving now by SiPearl, France bases start-up, just rai

Philippe Notton, CEO and founder, tells The Next Platform, the number of engineers working on the SiPearl Arm server chips – Rhea is the first generation and Chronos is the second generation – will grow to around 200 over the next two years as Rhea is created, tested, and ramped.

As to why Arm and not another core? For RISC-V, it is too early, and definitely so for a general purpose processor. X86 is not officially licensable and it is a bit too US-centric for what we are doing. And for us, Arm is much more neutral and what they are doing for HPC makes a lot of sense.”

The Rhea chip will support both DDR4 and DDR5 main memory as well as HBM main memory, PCI-Express 5.0 peripheral controllers and will support the CCIX protocol for hoking up accelerators over PCI-Express.

More about EPI
https://www.european-processor-initiative.eu/general-purpose-processor/
EPI platform
For Russian speaking only, sorry for inconvenience

Russian telecom company Metrotek announced session of online webinars "Introduction to FPGA development".
This course is for beginners and free of charge. The very first lecture starts at 11th of May. See details below:
https://habr.com/ru/post/500770
Take a part if you wish don't look stupid with question "How can I launch my cpp code on FPGA" :)

PS: It's not a commercial promo, if you wish to share similar trainings in English, we will do it with pleasure.
2025/07/03 21:39:03
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