Arteris Articles

SemiWiki: Segmenting the Machine-Learning Hardware Market

Kurt Shuler, VP Marketing at Arteris IP, shares his 91 entries into finding every company and product that is active in the AI hardware space in this latest SemiWiki blog:

Segmenting the Machine-Learning Hardware Market

March 13th, 2019 - By Bernard Murphy

Machine learning is everywhere, but it can be difficult at times to understand what that really means. Bernard Murphy (SemiWiki) talked to Kurt Shuler and dug through a very detailed spreadsheet Kurt developed to understand better better what is being used where in the ML market.

One of the great pleasures in what I do is to work with people who are working with people in some of the hottest design areas today. A second-level indirect to be sure but that gives me the luxury of taking a broad view. A recent discussion I had with Kurt Shuler (VP Marketing at Arteris IP) is in this class. As a conscientious marketing guy, he wants to understand the available market in AI hardware because they have quite a bit of activity in that space – more on that later. So Kurt put a lot of work into finding every company and product he could that is active in this space, 91 entries in his spreadsheet. This he broke down by company, territory (eg China or US), product, target market (eg vision or speech), implementation (eg FPGA or ASIC), whether the product is used in datacenters or at the edge and whether it is being used for training or inference. 


 For more information, download this FlexNoC AI Package datasheet; http://www.arteris.com/flexnoc-ai-package

Topics: FPGA semiconductor edge computing semiwiki inference kurt shuler flexnoc ai package AI training noc interconnect

SemiWiki: Safety: Big Opportunity, A Long and Hard Road

Kurt Shuler, VP Marketing at Arteris IP, explains the support and business cycle from the vendor to the integrator in the latest SemiWiki blog written by Bernard Murphy:

Safety: Big Opportunity, A Long and Hard Road

February 27th, 2019 - By Bernard Murphy

Still think you want to sell IP into the automotive chain? Bernard Murphy (SemiWiki) distills Kurt Shuler insights into what this takes. There’s certainly a lot of promise. More big chips in the central brain and in intelligent sensors together offer a lot of opportunity. The US, Europe and Israel markets are all very aggressive in developing ADAS and ML. China has been a laggard but is coming on strong and is not held back by legacy so much. They also see a big tie-in with AI where they are very strong. Kurt says there are more than a couple of hundred funded startups in automotive and AI in China.

That said, this is not an easy way to get rich. You’ll have to put a lot of investment into supporting your customers, supporting their customers and so on up to the top. The market is very dynamic, so what “done” means may not always be clear. You may not be paid for quite a long time. But if you have the grit to hang on and keep your customer happy the whole way through, you might just be successful!


 For more information, download this FlexNoC AI Package datasheet; http://www.arteris.com/flexnoc-ai-package

Topics: ISO 26262 semiconductor semiwiki kurt shuler flexnoc ai package noc interconnect ML-centric design

Semiconductor Engineering: The Race To Multi-Domain SoCs

 Arteris IP's CEO looks at how automotive and AI are Altering chip design in this article in Semiconductor Engineering;

The Race To Multi-Domain SoCs

February 7th,  2019 - By Ed Sperling

K. Charles Janac, president and CEO of Arteris IP, sat
down with Semiconductor Engineering to discuss the impact of automotive and AI on chip design. What follows are excerpts of that conversation.

SE: What do you see as the biggest changes over the next 12 to 24 months?
Janac: There are segments of the semiconductor market that are shrinking, such as DTV and simple IoT. Others are going through an investment phase, including automotive, AI/machine learning and China. You really want to be focused on those segments. 

SE: So does IP that’s being developed today look radically different than it did five years ago?
Janac:
Yes, everything is getting amazingly complex. What people are building right now are multi-domain SoCs. The CPU, which used to do all the work, does relatively less work. There are accelerators for vision and data analysis outside of the CPU subsystem. There are machine learning sections, some general-purpose, some very specific, all on-chip. There is a memory subsystem with very high-bandwidth memory and low latency. There also is functional safety. You need tremendous performance because a car is a supercomputer on wheels. The car has to be very efficient, because you need to deliver that compute power without water cooling. Power management becomes very sophisticated. And then there are functional safety and security subsystems to keep these safe from environmental and man-made issues.

SE: Where does the network on chip (NoC) fit into all of this?
Janac: All data goes through the NoC of the chip. There are opportunities for generating value from that. But the increase in complexity is increasing the number and sophistication of the interconnect parts of the chip. Before, you may have had networks on chip. Now you may have 20 or 30.

Topics: semiconductor automotive ADAS neural networks AI LIDAR flexnoc ai package noc interconnect ML AI SoC Designers chiplets

Semiconductor Engineering: ISO 26262:2018, 2nd Edition: What Changes?

 Arteris IP's Kurt Shuler, vice president of marketing, delivers a recent update for the ISO 26262 standard in this blog in Semiconductor Engineering;

ISO 26262:2018, 2nd Edition: What changes?

February 7th,  2019 - By Kurt Shuler

The safety standard is now clearer for IP-based designs and those happening across multiple companies.

If you’re involved somehow in design for automotive electronics, you probably have more than a cursory understanding of the ISO 26262 standard. What your organization is working from is most likely the 2011 definition. The most recent update is formally known as ISO 26262:2018, less formally as ISO 26262 2nd Edition.

Standards should evolve, but what changed and why? I’ve been a member of the ISO 26262 working group for many years, and particularly involved in how it should be interpreted for IP, and I’ve got to tell you, I have struggled. 

From my perspective, it was originally written around an implicit expectation that chips are built from scratch entirely within one organization, and this is a dated assumption. There was also not enough guidance for IP-based design or design distributed across multiple companies or sites. The workaround for an IP supplier has been to use the Safety Element out of Context (SEooC) mechanism. But this depends heavily on human interpretation, by the component vendor on what may be relevant to the integrator and vice-versa, with little guidance from the 2011 version of the standard. I complained (whined?) quite a bit to the committee about these problems and they eventually invited me to the working group. I wasn’t the only one confused and other people joined, and we seem to have had an impact; our efforts have resulted in a lot more clarification, organization and practical examples in the latest standard. I think the new Part 11 of the updated standard provides a lot more detail and useful examples for us in the semiconductor and semiconductor IP industry.

For more information about ISO 26262:2018 Part 11, download the 39-slide Arm TechCon presentation titled, “Fundamentals of ISO 26262 Part 11 for Semiconductors,” by Arteris IP Functional Safety Manager Alexis Boutillier and ResilTech Scientific Advisor Dr. Andrea Bondavalli, or watch my very popular SemiEngineering “Tech Talk: ISO 26262 Drilldown” video.

Topics: semiconductor automotive neural networks ISO 26262 certification AI AI chips flexnoc ai package noc interconnect ML AI SoC Designers