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December 2, 2022
Amazon’s AWS Extends Computing Options and Services

November 18, 2022
Qualcomm Extends Its Reach Beyond the Smartphone

October 25, 2022
Lenovo Drives Form Factor Innovations in PC and XR

October 21, 2022
Cloudera Extends Open Data Lakehouse Benefits to Hybrid Cloud

October 11, 2022
Google Unveils a Host of Open Data and AI Advancements at Cloud Next

October 5, 2022
From PCs to Cars: Nvidia, Qualcomm & Intel Race to Automotive Semis

September 14, 2022
Intel Highlights Key PC Platform Innovations for 13th Gen Core CPUs

September 1, 2022
VMware’s vSphere 8 Brings DPUs from AMD, Intel, and Nvidia to Life

August 17, 2022
Cloudera CDP One Brings Advanced Data Management to the Mainstream

August 10, 2022
IBM Research Tech Makes Edge AI Applications Scalable

July 20, 2022
Amazon Extends Alexa’s Reach with New Tools

July 19, 2022
Qualcomm Accelerates Wearables with W5 Platforms

July 12, 2022
New Research Highlights Opportunities and Challenges for Private 5G

June 29, 2022
Arm Aims to Make Mobile Graphics “Immortal-is”

June 14, 2022
Cisco Brings Simplicity and Observability to Networks, Collaboration and Cloud Apps

May 24, 2022
Microsoft Unveils Foundation for AI-Powered Client/Cloud Hybrid Loop

May 18, 2022
Citrix to Integrate with Microsoft Windows 365

May 3, 2022
Dell Expands APEX, Adds Analytics and Data Recovery

April 27, 2022
Arm Simplifies and Modernizes IoT Development with Virtual Hardware

April 21, 2022
Amazon’s Launch of Buy with Prime Highlights Growth of Logistics Business

March 30, 2022
Intel Spices Up PC Market with Arc GPU Launch

March 22, 2022
Nvidia GTC Announcements Confirm it’s a Connected, Multi-Chip World

March 15, 2022
Lenovo and AMD Announcements Highlight Spring PC Refresh

March 8, 2022
The Future of Semiconductors is UCIe

March 2, 2022
Qualcomm Demos Future of Connectivity with WiFi 7 and X70 5G Chips

February 24, 2022
5G Edge Computing Challenges Remain

February 9, 2022
Samsung Raises the Bar with Ultra Versions of S22 and Tab S8

January 20, 2022
US 5G Market Just Got Much More Interesting

January 4, 2022
Qualcomm Extends Automotive Offerings with Snapdragon Ride Vision, Digital Chassis

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TECHnalysis Research Blog

December 6, 2022
Lattice Semi Expands to Mid-Range FPGAs with Avant Line

By Bob O'Donnell

When you have a product that’s challenging to explain, it often helps to give simple examples to help people understand what it does and why it matters. Such is the case with a specialized type of semiconductor chip known as FPGAs (Field Programmable Gate Arrays), a powerful, but little understood component that’s used in everything from PCs and servers to industrial machines, telecom networks, and military equipment. At the launch of a new mid-range line of FPGAs from Lattice Semiconductor, the company used this approach, highlighting a straightforward visual demo of its new chip identifying and tracking vehicles from the camera of a connected car, a critical capability for assisted and autonomous driving features.

As the name suggests, FPGAs can be customized and programmed to perform certain functions directly in hardware. This gives them important performance advantages for a number of specific applications. Even better, they can be reprogrammed after they’ve been installed, making them ideal not only for developing products (which demand new software and hardware updates all the time), but also for adding new capabilities to existing products. In the world of AI and edge computing, for example, it’s not at all uncommon to have algorithms for doing things such as identifying and tracking objects being updated on a regular basis. FPGAs can be ideal for these kinds of applications precisely because of their programmability.

Over the past few years, Lattice Semi has focused its efforts on creating a full line of tiny, low power FPGAs it calls Nexus. In addition, the company has evolved its software offerings, creating a range of development tools such as Radiant and Propel, as well as a full suite of software platforms, such as SenseAI, mVision and ORAN, which are optimized for specific markets or applications. As successful as Lattice Semi has been with its low-power Nexus line, the overall category only represents about 1/3 of the total FPGA market. Another third belongs to what’s termed mid-range FPGAs, which offer more performance than their low-power brethren, but require more energy to run.

Not surprisingly, Lattice Semi’s latest move brings them into this mid-range market with a new line of FGPAs dubbed Avant. These new chips offer a 5x improvement in capacity, 10x increase in bandwidth, and 30x jump in performance versus the Nexus line. Importantly, the new Avant chips work with all the company’s existing software, making the transition process easy for existing customers and allowing them to leverage their software development work.

In addition, from a competitive perspective, Lattice Semi claims that the performance of Avant is 2x faster and 2.5x more power efficient than similar chips from Intel (Altera/Stratix) and AMD (Xilinx, which AMD recently acquired). The Avant chips are also 6x smaller than competitors, which potentially makes them usable on circuit boards and in designs that other larger chips wouldn’t be able to fit in.

As with its Nexus line, Lattice Semi said that they plan to introduce a whole range of products to its Avant line (and will still, by the way, make new additions to its ongoing Nexus line). The first chip is called Avant-E and it’s been optimized for edge computing applications, though the company was quick to point out that it can (and is) being used in other types of applications as well. The top-of-the-line Avant-E 500 offers 5 TOPS (tera operations per second) of performance for AI-related applications running at a 350 MHz clock rate. In theory, this makes it well suited to run AI inferencing applications in edge computing devices, a field that looks like it will finally start to get some real traction over the next year or two. Plus, the Avant FPGAs integrate several security-specific hardware features, potentially making them a more attractive option for certain applications or hardware designs than other general purpose AI accelerators without integrated security.

What’s potentially even more compelling is that AI-based deep learning and neural network algorithms that are built with popular machine learning frameworks like Pytorch, Caffe, TensorFlow, etc. can be ported to work on these new chips thanks to the latest version of Lattice Semi’s SenseAI software platform. The Lattice Semi software can basically import the high-level framework output and translate it into the instructions needed by the FPGA. This is a big deal, because few AI algorithm creators have much experience with FPGAs—the chips used to be somewhat notorious as very difficult to write software for—meaning there’s a wealth of new programmers and applications that could start using the more powerful Avant line.

As appealing as the technology sounds, it’s important to note that FPGAs don’t necessarily work for every application. However, they are a potential solution (or at least part of a solution) for a significantly wider array of companies, devices, and applications than they currently serve, particularly in situations where flexibility and upgradability are key.

With the debut of its new Avant line, Lattice Semi is significantly growing its potential market and morphing itself into a more complete FPGA provider. Big name competitors like Intel and AMD certainly aren’t going to shy away because of it, though, so the company needs to continue to innovate. Still, it’s clear that the future of FPGAs overall, and Lattice Semi in particular, are starting to look a lot more interesting.

Here’s a link to the original column: https://www.linkedin.com/pulse/lattice-semi-expands-mid-range-fpgas-avant-line-bob-o-donnell

Bob O’Donnell is the president and chief analyst of TECHnalysis Research, LLC a market research firm that provides strategic consulting and market research services to the technology industry and professional financial community. You can follow him on LinkedIn at Bob O’Donnell or on Twitter @bobodtech.

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