#FPGA Companies

[chandupalle]

[364 Pages Report] The FPGA market was valued at USD 12.1 billion in 2024 and is estimated to reach USD 25.8 billion by 2029, registering a CAGR of 16.4% during the forecast period.

[volersystems]

Apart from the FPGA design, Voler Systems formulated the necessary firmware for board functionality testing that enabled to customer to finalize their firmware development. Voler Systems worked closely with their mechanical design team to match the device’s electrical, mechanical, and environmental requirements. Their engineers made sure that the device was functional, durable, and reliable under the extreme conditions, often common during military operations.

[andmaybegayer]

What are some of the coolest computer chips ever, in your opinion?

Hmm. There are a lot of chips, and a lot of different things you could call a Computer Chip. Here's a few that come to mind as "interesting" or "important", or, if I can figure out what that means, "cool".

If your favourite chip is not on here honestly it probably deserves to be and I either forgot or I classified it more under "general IC's" instead of "computer chips" (e.g. 555, LM, 4000, 7000 series chips, those last three each capable of filling a book on their own). The 6502 is not here because I do not know much about the 6502, I was neither an Apple nor a BBC Micro type of kid. I am also not 70 years old so as much as I love the DEC Alphas, I have never so much as breathed on one.

Disclaimer for writing this mostly out of my head and/or ass at one in the morning, do not use any of this as a source in an argument without checking.

Intel 3101

So I mean, obvious shout, the Intel 3101, a 64-bit chip from 1969, and Intel's first ever product. You may look at that, and go, "wow, 64-bit computing in 1969? That's really early" and I will laugh heartily and say no, that's not 64-bit computing, that is 64 bits of SRAM memory.

This one is cool because it's cute. Look at that. This thing was completely hand-designed by engineers drawing the shapes of transistor gates on sheets of overhead transparency and exposing pieces of crudely spun silicon to light in a """"cleanroom"""" that would cause most modern fab equipment to swoon like a delicate Victorian lady. Semiconductor manufacturing was maturing at this point but a fab still had more in common with a darkroom for film development than with the mega expensive building sized machines we use today.

As that link above notes, these things were really rough and tumble, and designs were being updated on the scale of weeks as Intel learned, well, how to make chips at an industrial scale. They weren't the first company to do this, in the 60's you could run a chip fab out of a sufficiently well sealed garage, but they were busy building the background that would lead to the next sixty years.

Lisp Chips

This is a family of utterly bullshit prototype processors that failed to be born in the whirlwind days of AI research in the 70's and 80's.

Lisps, a very old but exceedingly clever family of functional programming languages, were the language of choice for AI research at the time. Lisp compilers and interpreters had all sorts of tricks for compiling Lisp down to instructions, and also the hardware was frequently being built by the AI researchers themselves with explicit aims to run Lisp better.

The illogical conclusion of this was attempts to implement Lisp right in silicon, no translation layer.

Yeah, that is Sussman himself on this paper.

These never left labs, there have since been dozens of abortive attempts to make Lisp Chips happen because the idea is so extremely attractive to a certain kind of programmer, the most recent big one being a pile of weird designd aimed to run OpenGenera. I bet you there are no less than four members of r/lisp who have bought an Icestick FPGA in the past year with the explicit goal of writing their own Lisp Chip. It will fail, because this is a terrible idea, but damn if it isn't cool.

There were many more chips that bridged this gap, stuff designed by or for Symbolics (like the Ivory series of chips or the 3600) to go into their Lisp machines that exploited the up and coming fields of microcode optimization to improve Lisp performance, but sadly there are no known working true Lisp Chips in the wild.

Zilog Z80

Perhaps the most important chip that ever just kinda hung out. The Z80 was almost, almost the basis of The Future. The Z80 is bizzare. It is a software compatible clone of the Intel 8080, which is to say that it has the same instructions implemented in a completely different way.

This is, a strange choice, but it was the right one somehow because through the 80's and 90's practically every single piece of technology made in Japan contained at least one, maybe two Z80's even if there was no readily apparent reason why it should have one (or two). I will defer to Cathode Ray Dude here: What follows is a joke, but only barely

The Z80 is the basis of the MSX, the IBM PC of Japan, which was produced through a system of hardware and software licensing to third party manufacturers by Microsoft of Japan which was exactly as confusing as it sounds. The result is that the Z80, originally intended for embedded applications, ended up forming the basis of an entire alternate branch of the PC family tree.

It is important to note that the Z80 is boring. It is a normal-ass chip but it just so happens that it ended up being the focal point of like a dozen different industries all looking for a cheap, easy to program chip they could shove into Appliances.

Effectively everything that happened to the Intel 8080 happened to the Z80 and then some. Black market clones, reverse engineered Soviet compatibles, licensed second party manufacturers, hundreds of semi-compatible bastard half-sisters made by anyone with a fab, used in everything from toys to industrial machinery, still persisting to this day as an embedded processor that is probably powering something near you quietly and without much fuss. If you have one of those old TI-86 calculators, that's a Z80. Oh also a horrible hybrid Z80/8080 from Sharp powered the original Game Boy.

I was going to try and find a picture of a Z80 by just searching for it and look at this mess! There's so many of these things.

I mean the C/PM computers. The ZX Spectrum, I almost forgot that one! I can keep making this list go! So many bits of the Tech Explosion of the 80's and 90's are powered by the Z80. I was not joking when I said that you sometimes found more than one Z80 in a single computer because you might use one Z80 to run the computer and another Z80 to run a specialty peripheral like a video toaster or music synthesizer. Everyone imaginable has had their hand on the Z80 ball at some point in time or another. Z80 based devices probably launched several dozen hardware companies that persist to this day and I have no idea which ones because there were so goddamn many.

The Z80 eventually got super efficient due to process shrinks so it turns up in weird laptops and handhelds! Zilog and the Z80 persist to this day like some kind of crocodile beast, you can go to RS components and buy a brand new piece of Z80 silicon clocked at 20MHz. There's probably a couple in a car somewhere near you.

Pentium (P6 microarchitecture)

Yeah I am going to bring up the Hackers chip. The Pentium P6 series is currently remembered for being the chip that Acidburn geeks out over in Hackers (1995) instead of making out with her boyfriend, but it is actually noteworthy IMO for being one of the first mainstream chips to start pulling serious tricks on the system running it.

The P6 microarchitecture comes out swinging with like four or five tricks to get around the numerous problems with x86 and deploys them all at once. It has superscalar pipelining, it has a RISC microcode, it has branch prediction, it has a bunch of zany mathematical optimizations, none of these are new per se but this is the first time you're really seeing them all at once on a chip that was going into PC's.

Without these improvements it's possible Intel would have been beaten out by one of its competitors, maybe Power or SPARC or whatever you call the thing that runs on the Motorola 68k. Hell even MIPS could have beaten the ageing cancerous mistake that was x86. But by discovering the power of lying to the computer, Intel managed to speed up x86 by implementing it in a sensible instruction set in the background, allowing them to do all the same clever pipelining and optimization that was happening with RISC without having to give up their stranglehold on the desktop market. Without the P5 we live in a very, very different world from a computer hardware perspective.

From this falls many of the bizzare microcode execution bugs that plague modern computers, because when you're doing your optimization on the fly in chip with a second, smaller unix hidden inside your processor eventually you're not going to be cryptographically secure.

RISC is very clearly better for, most things. You can find papers stating this as far back as the 70's, when they start doing pipelining for the first time and are like "you know pipelining is a lot easier if you have a few small instructions instead of ten thousand massive ones.

x86 only persists to this day because Intel cemented their lead and they happened to use x86. True RISC cuts out the middleman of hyperoptimizing microcode on the chip, but if you can't do that because you've girlbossed too close to the sun as Intel had in the late 80's you have to do something.

The Future

This gets us to like the year 2000. I have more chips I find interesting or cool, although from here it's mostly microcontrollers in part because from here it gets pretty monotonous because Intel basically wins for a while. I might pick that up later. Also if this post gets any longer it'll be annoying to scroll past. Here is a sample from a post I have in my drafts since May:

I have some notes on the weirdo PowerPC stuff that shows up here it's mostly interesting because of where it goes, not what it is. A lot of it ends up in games consoles. Some of it goes into mainframes. There is some of it in space. Really got around, PowerPC did.

[moremarketresearch]

Global AI Accelerator Chip Market Expected to Grow Substantially Owing to Healthcare Industry

Global AI Accelerator Chip Market Expected to Grow Substantially Owing to Increased Use of AI Accelerator Chips in Healthcare Industry. The global AI accelerator chip market is expected to grow primarily due to its growing use in the healthcare industry. The cloud sub-segment is expected to flourish immensely. The market in the North American region is predicted to grow with a high CAGR by 2031. NEW YORK, March 17, 2023 - As per the report published by Research Dive, the global AI accelerator chip market is expected to register a revenue of $332,142.7 million by 2031 with a CAGR of 39.3% during the 2022-2031 period.

Dynamics of the Global AI Accelerator Chip Market

Growing use of AI accelerator chips across the global healthcare industry is expected to become the primary growth driver of the AI accelerator chip market in the forecast period. Additionally, the rise of the cyber safety business is predicted to propel the market forward. However, according to market analysts, lack of skilled AI accelerator chip workforce might become a restraint in the growth of the market. The growing use of AI accelerator chip semiconductors is predicted to offer numerous growth opportunities to the market in the forecast period. Moreover, the increased use of AI accelerator chips to execute AI workloads such as neural networks is expected to propel the AI accelerator chip market forward in the coming period.

COVID-19 Impact on the Global AI Accelerator Chip Market

The Covid-19 pandemic disrupted the routine lifestyle of people across the globe and the subsequent lockdowns adversely impacted the industrial processes across all sectors. The AI accelerator chip market, too, was negatively impacted due to the pandemic. The disruptions in global supply chains due to the pandemic resulted in a decline in the semiconductor manufacturing industry. Also, the travel restrictions put in place by various governments reduced the availability of skilled workforce. These factors brought down the growth rate of the market.

Key Players of the Global AI Accelerator Chip Market

The major players in the market include: - NVIDIA Corporation - Micron Technology Inc. - NXP Semiconductors N.V. - Intel Corporation - Microsoft Corporation - Advanced Micro Devices Inc. (AMD) - Qualcomm Technologies Inc. - Alphabet Inc. (Google Inc.) - Graphcore Limited. - International Business Machines Corporation These players are working on developing strategies such as product development, merger and acquisition, partnerships, and collaborations to sustain market growth. For instance, in May 2022, Intel Habana, a subsidiary of Intel, announced the launch of 2nd generation AI chips which according to the company, will provide a 2X performance advantage over the previous generation NVIDIA A100. This product launch will help Intel Habana to capitalize on this rather nascent market and will consolidate its lead over the competitors further.

What the Report Covers:

Apart from the information summarized in this press release, the final report covers crucial aspects of the market including SWOT analysis, market overview, Porter's five forces analysis, market dynamics, segmentation (key market trends, forecast analysis, and regional analysis), and company profiles (company overview, operating business segments, product portfolio, financial performance, and latest strategic moves and developments.)

Segments of the AI Accelerator Chip Market

The report has divided the AI accelerator chip market into the following segments: Chip Type: Graphics Processing Unit (GPU), Application-Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGA), Central Processing Unit (CPU), and others Processing Type: edge and cloud Application: Natural Language Processing (NLP), computer vision, robotics, and network security Industry Vertical: financial services, automotive and transportation, healthcare, retail, telecom, and others Region: North America, Europe, Asia-Pacific, and LAMEA SegmentSub-SegmentChip TypeCentral Processing Unit (CPU) – Most dominant market share in 2021 - The use of CPU for improving the performance of a computer while running graphics and video editors are expected to push the growth of this sub-segment further.Processing TypeCloud – Significant revenue growth in 2021 Cloud acceleration chip helps content creators, publishers, and other entities to offer material to end users promptly which is predicted to propel the growth rate of the market higher.ApplicationNatural Language Processing (NLP) – Highest market share in 2021 Increased use of Natural Language Processing (NLP) due to its ability to make computer-human interactions more natural is expected to propel the sub-segment forward.Industry VerticalHealthcare– Huge market revenue in 2021 The growing use of AI by major healthcare companies to complement medical imaging is anticipated to offer numerous growth opportunities to the sub-segment in the forecast period.RegionNorth America – Most profitable by 2031 The development of new technologies in artificial intelligence (AI) accelerators in this region is predicted to propel the market in the forecast period. Read the full article

[anidealvenue]

A list of Automotive Engineering Service Companies in Germany

Bertrandt AG, https://www.bertrandt.com/. Bertrandt operates in digital engineering, physical engineering, and electrical systems/electronics segments. Its Designing function includes designing of all the elements of the automotive.

Alten Group, https://www.alten.com/. ALTEN Group supports the development strategy of its customers in the fields of innovation, R&D and technological information systems. Created 30 years ago, the Group has become a world leader in Engineering and Technology consulting. 24 700 highly qualified engineers carry out studies and conception projects for the Technical and Information Systems Divisions of major customers in the industrial, telecommunications and Service sectors.

L&T Technology Services Limited, https://www.ltts.com/. LTTS’ expertise in engineering design, product development, smart manufacturing, and digitalization touches every area of our lives — from the moment we wake up to when we go to bed. With 90 Innovation and R&D design centers globally, we specialize in disruptive technology spaces such as EACV, Med Tech, 5G, AI and Digital Products, Digital Manufacturing, and Sustainability.

FEV Group GmbH, https://www.fev.com/. FEV is into the design and development of internal combustion engines, conventional, electric, and alternative vehicle drive systems, energy technology, and a major supplier of advanced testing and instrumentation products and services to some of the world’s largest powertrain OEMs. Founded in 1978 by Prof. Franz Pischinger, today the company employs worldwide highly skilled research and development specialists on several continents.

Harman International, https://www.harman.com/. HARMAN designs and engineers connected products and solutions for automakers, consumers, and enterprises worldwide, including connected car systems, audio and visual products, enterprise automation solutions; and services supporting the Internet of Things.

EDAG Engineering GmbH, https://www.edag.com/de/. EDAG is into vehicle development, plant planning and construction, and process optimization.

HCL Technologies Limited, http://www.hcltech.com/. HCL Technologies Limited is an Indian multinational information technology services and consulting company headquartered in Noida. It emerged as an independent company in 1991 when HCL entered into the software services business. The company has offices in 52 countries and over 210,966 employees.

Cientra GmbH, https://www.cientra.com/. Cientra expertise across VLSI, ASIC, FPGA, SoC engineering, and IoT accelerate our delivery of customized solutions to the Consumer, Aviation, Semiconductors, Telecom, Wireless, and Automotive industries across their product lifecycle.

Akka Technologies, https://www.akka-technologies.com/. AKKA supports the world’s leading industry players in their digital transformation and throughout their entire product life cycle.

IAV GmbHb, https://www.iav.com/en/. IAV develops the mobility of the future. Regardless of the specific manufacturer, our engineering proves itself in vehicles and technologies all over the world.

Altran Technologies, https://www.altran.com/in/en/. Altran expertise from strategy and design to managing operations in the fields of cloud, data artificial intelligence, connectivity, software, digital engineering, and platforms.

Capgemini Engineering, https://capgemini-engineering.com/de/de/. Capgemini Engineering is a technology and innovation consultancy across sectors including Aeronautics, Space, Defense, Naval, Automotive, Rail, Infrastructure & Transportation, Energy, Utilities & Chemicals, Life Sciences, Communications, Semiconductor & Electronics, Industrial & Consumer, Software & Internet.

[codeshive]

ECE454 Homework1: Profiling and Compiler Optimizations solved

1 Introduction Upon graduation from Skule, and having become a high-performance program-optimizing guru, you decided to open your own high-performance code optimization consulting firm, called “OptsRus”. OptsRus’ first client is a reconfigurable computing company that is using the open source CAD software program VPR (developed at UofT) to map customer designs to their reconfigurable FPGA-like…

[codingprolab]

ECE454 Homework1: Profiling and Compiler Optimizations

1 Introduction Upon graduation from Skule, and having become a high-performance program-optimizing guru, you decided to open your own high-performance code optimization consulting firm, called “OptsRus”. OptsRus’ first client is a reconfigurable computing company that is using the open source CAD software program VPR (developed at UofT) to map customer designs to their reconfigurable FPGA-like…

[navsooch]

Autonomous Systems Advancements: Semiconductor Sensors and Processing with Industry Leaders including Nav Sooch

The semiconductor industry is at the forefront of revolutionizing modern technology, particularly with the rapid advancements in autonomous systems. These systems, ranging from self-driving vehicles to smart home devices, rely heavily on semiconductor sensors and processing capabilities to function effectively. As these technologies evolve, the semiconductor industry is adapting and innovating to meet the growing demands for precision, speed, and reliability. This blog explores the latest trends in semiconductor sensors and processing technologies that are driving advancements in autonomous systems.

Evolution of Semiconductor Sensors

Semiconductor sensors have undergone significant evolution in recent years, driven by the increasing complexity and capabilities required for autonomous systems. Initially designed for simple tasks, these sensors are now capable of providing highly detailed and accurate data, essential for the functioning of autonomous systems. Modern semiconductor sensors include advanced features such as enhanced sensitivity, lower power consumption, and improved integration with other system components.

The integration of sensors into autonomous systems involves the use of various technologies, including lidar, radar, and cameras. These sensors collect data from the environment, which is then processed to make real-time decisions. Professionals like Nav Sooch mention that the continuous advancements in semiconductor technology enable these sensors to deliver higher resolution data and operate in diverse conditions, thus enhancing the performance and safety of autonomous systems.

Advances in Semiconductor Processing Technologies

The processing power of semiconductors is crucial for handling the vast amounts of data generated by sensors in autonomous systems. Recent advancements in semiconductor processing technologies have led to the development of more powerful and efficient processors. These processors are designed to manage complex algorithms and data processing tasks with greater speed and accuracy.

One notable trend is the shift towards application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs). ASICs are custom-designed chips optimized for specific tasks, offering enhanced performance and efficiency. FPGAs, on the other hand, provide flexibility and can be reconfigured to adapt to changing requirements. Both technologies play a significant role in improving the capabilities of autonomous systems by enabling faster and more efficient data processing as highlighted by leaders such as Nav Sooch.

Integration of AI and Machine Learning

Artificial intelligence (AI) and machine learning (ML) are transforming the semiconductor industry by enabling more sophisticated processing capabilities. The integration of AI and ML algorithms into semiconductor devices enhances their ability to learn from data and make intelligent decisions. Industry leaders including Nav Sooch convey that this integration is particularly important for autonomous systems, where real-time data analysis and decision-making are critical.

Semiconductor companies are developing specialized AI chips designed to accelerate machine learning tasks. These chips are optimized for parallel processing, enabling them to handle large volumes of data and perform complex computations quickly. The combination of AI and semiconductor technology is driving advancements in autonomous systems, leading to improved accuracy, reliability, and overall performance.

Enhancements in Power Efficiency

Power efficiency is a critical consideration in the design of semiconductor components for autonomous systems. As these systems become more advanced, they require more power to operate, making energy efficiency a key focus for semiconductor manufacturers. Recent developments in semiconductor technology have led to the creation of more power-efficient components as pointed out by professionals like Nav Sooch, which help extend the operational life of autonomous systems and reduce their overall energy consumption.

Innovations such as low-power processing units and energy-efficient sensors contribute to the overall efficiency of autonomous systems. By minimizing power consumption, semiconductor devices help reduce heat generation and improve system reliability. Additionally, advancements in power management techniques, such as dynamic voltage and frequency scaling, further enhance the energy efficiency of semiconductor components.

Impact of 5G on Semiconductor Advancements

The rollout of 5G technology is having a profound impact on the semiconductor industry, particularly in the context of autonomous systems. 5G networks offer significantly higher data transfer speeds and lower latency compared to previous generations, enabling faster and more reliable communication between autonomous devices.

Semiconductor components must be designed to support the high-speed data transmission required by 5G networks. This includes developing advanced communication chips and ensuring compatibility with 5G infrastructure. The integration of 5G technology enhances the performance of autonomous systems by enabling real-time data exchange and improving connectivity, which is essential for applications such as autonomous vehicles and smart cities.

Future Trends and Innovations

Looking ahead, the semiconductor industry is expected to continue evolving with ongoing innovations and emerging technologies. Future trends include the development of more advanced sensors, increased integration of AI and machine learning, and further enhancements in power efficiency and connectivity.

Leaders such as Nav Sooch express that researchers and engineers are exploring new materials and fabrication techniques to push the boundaries of semiconductor performance. Additionally, the growing demand for autonomous systems is driving investments in research and development, leading to the creation of cutting-edge technologies. As these advancements unfold, they will shape the future of autonomous systems and the broader semiconductor industry.

The advancements in semiconductor sensors and processing technologies are pivotal in driving the progress of autonomous systems. From enhanced sensor capabilities and powerful processors to the integration of AI and machine learning, these developments are shaping the future of technology. As the semiconductor industry continues to innovate and adapt, the potential for autonomous systems to revolutionize various aspects of our lives becomes increasingly promising. Embracing these trends and staying abreast of technological advancements will be crucial for stakeholders in the semiconductor and autonomous systems sectors.

[semiconductorsandelectronics]

Field Programmable Gate Arrays (FPGAs) are integral to the evolving landscape of digital technologies, offering flexible and reconfigurable hardware solutions for a range of applications.

[nawapon17]

[News] Intel Reportedly Mulls to Sell FPGA Unit Altera and Freeze USD 32 Billion German Project amid Crisis | TrendForce Insights

[veer-acl]

ACL Digital is Your Preferred Partner for Semiconductor Solutions in the USA

Embedded systems and semiconductor technology have converged, reshaping our interactions with the world. Continuous innovation in the semiconductor industry is driving technological breakthroughs, creating a more innovative, highly connected world. ACL Digital provides high-performance, cost-effective, and reliable hardware and software solutions for OEMs and enterprises.

Comprehensive Semiconductor Services in the USA

ACL Digital empowers your chip design journey with a full spectrum of services, including VLSI IPs, ASICs, SoCs, and FPGAs. From architecture to RTL design, verification, and GDSII, our engineering team is at the forefront of innovation. We focus on low-power, high-speed, and area-efficient designs to deliver advanced solutions globally.

Key Highlights of Our Semiconductor Practice

In-House Capabilities

We build next-generation semiconductor solutions in the USA, from initial chip design to cutting-edge silicon and embedded software.

Seamless Integration

Our design and test engineering processes enable optimized costs and maximized performance.

End-to-End Services

We offer chip design, verification, IP integration, and embedded software solutions, ensuring the highest ROI on R&D investments.

ACL Digital’s Semiconductor Offerings

VLSI Design and Engineering

Advanced VLSI solutions and engineering expertise, from RTL design and architecture to FIP.

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Comprehensive services from pre-silicon to post-silicon validation, solution engineering, pro-support/IDH, and more.

Why Choose ACL Digital

Expert in Semiconductor Solutions

We lead in design-led semiconductor engineering, product engineering, and digital experience services.

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Collaborations with NXP, Marvell, Texas Instruments, Silicon Labs, ARM, and others provide full development cycle support.

Technological Advancements

Market readiness and early access to cutting-edge platforms give our clients a competitive edge.

Centers of Excellence (CoEs)

Expertise in RISC-V, ARM, TSMC, and Functional Safety (FuSa) ensures cutting-edge design solutions.

Advanced Technology Expertise

Deep understanding of SoC system blocks, CPU subsystems, high-speed IOs, low-speed IOs, and analog/mixed-signal designs.

Industry Expert

Trusted partner for pre-silicon, platform software, and solution engineering, providing unwavering technical support.

ACL Digital stands out among semiconductor chip design companies, offering top-tier semiconductor solutions and semiconductor services in the USA. You can partner with us to navigate the complexities of the semiconductor industry and drive your technological advancements forward.

Contact Us Today

Discover how ACL Digital can elevate your semiconductor solutions in the USA. Contact us to learn more about our services and how we can help you achieve your goals.

[chandupalle]

FPGA Companies - Advanced Micro Devices (Xilinx, Inc.) (US) and Intel Corporation (US) are the Key Players

 The FPGA market is projected to grow from USD 12.1 billion in 2024 and is projected to reach USD 25.8 billion by 2029; it is expected to grow at a CAGR of 16.4% from 2024 to 2029.

The growth of the FPGA market is driven by the rising trend towards Artificial Intelligence (AI) and Internet of Things (IoT) technologies in various applications and the integration of FPGAs into advanced driver assistance systems (ADAS). 

Major FPGA companies include:

·         Advanced Micro Devices (Xilinx, Inc.) (US),

·         Intel Corporation (US),

·         Microchip Technology Inc. (US),

·         Lattice Semiconductor Corporation (US), and

·         Achronix Semiconductor Corporation (US).

Major strategies adopted by the players in the FPGA market ecosystem to boost their product portfolios, accelerate their market share, and increase their presence in the market include acquisitions, collaborations, partnerships, and new product launches.

For instance, in October 2023, Achronix Semiconductor Corporation announced a partnership with Myrtle.ai, introducing an accelerated automatic speech recognition (ASR) solution powered by the Speedster7t FPGA. This innovation enables the conversion of spoken language into text in over 1,000 real-time streams, delivering exceptional accuracy and response times, all while outperforming competitors by up to 20 times.

In May 2023, Intel Corporation introduced the Agilex 7 featuring the R-Tile chiplet. Compared to rival FPGA solutions, Agilex 7 FPGAs equipped with the R-Tile chiplet showcase cutting-edge technical capabilities, providing twice the speed in PCIe 5.0 bandwidth and four times higher CXL bandwidth per port.

ADVANCED MICRO DEVICES, INC. (FORMERLY XILINX, INC.):

AMD offers products under four reportable segments: Data Center, Client, Gaming, and Embedded Segments. The Data Center segment offers CPUs, GPUs, FPGAs, DPUs, and adaptive SoC products for data centers. The portfolio of the Client segment consists of APUs, CPUs, and chipsets for desktop and notebook computers. The Gaming segment provides discrete GPUs, semi-custom SoC products, and development services. The Embedded segment offers embedded CPUs, GPUs, APUs, FPGAs, and Adaptive SoC devices. AMD offers its products to a wide range of industries, including aerospace & defense, architecture, engineering & construction, automotive, broadcast & professional audio/visual, government, consumer electronics, design & manufacturing, education, emulation & prototyping, healthcare & sciences, industrial & vision, media & entertainment, robotics, software & sciences, supercomputing & research, telecom & networking, test & measurement, and wired & wireless communications. AMD focuses on high-performance and adaptive computing technology, FPGAs, SoCs, and software.

Intel Corporation:Intel Corporation, based in the US, stands as one of the prominent manufacturers of semiconductor chips and various computing devices. The company's extensive product portfolio encompasses microprocessors, motherboard chipsets, network interface controllers, embedded processors, graphics chips, flash memory, and other devices related to computing and communications. Intel Corporation boasts substantial strengths in investment, marked by a long-standing commitment to research and development, a vast manufacturing infrastructure, and a robust focus on cutting-edge semiconductor technologies. For instance, in October 2023, Intel announced an expansion in Arizona that marked a significant milestone, underlining its dedication to meeting semiconductor demand, job creation, and advancing US technological leadership. Their dedication to expanding facilities and creating high-tech job opportunities is a testament to their strategic investments in innovation and growth.

[volersystems]

A leading aerospace company experienced this challenge head-on while developing a wearable night vision camera designed for military operations. With strict requirements for size, weight, power consumption, and performance, the company required a trustworthy partner with specialized expertise. Voler Systems, well-known for its innovation in FPGA design, electronic design, wearables, and firmware, collaborated to bring this ambitious project to life.

[agnisystechnology]

Taking the First Step in Portable Stimulus Adoption

As chips get ever larger and more complex, one thing is for certain: the electronic design automation (EDA) tools, techniques, and methodologies used to develop silicon become more sophisticated. Every stage of chip development—architecture, design, implementation, verification, programming, validation, and test—consumes more time and resources. Continual improvement in EDA is the only way to avoid total project meltdown. This situation puts enormous pressure on Agnisys and other solutions providers to adopt the latest and greatest technologies to help our users succeed.

It’s easy to check off a list of development improvements that have helped over the years: automated layout, register transfer level (RTL) design, logic synthesis, constrained-random testbenches, formal and static verification, automated test pattern generation (ATPG), and more. It seems that every few years a new technique, guided by a comprehensive methodology, emerges to tackle the ever-rising size and complexity of designs. In recent times, perhaps no new approach holds more promise than the portable stimulus standard (PSS) developed by Accellera.

What is Portable Stimulus?

Verification has been the dominant phase of chip development for some time; most projects consume about two-thirds of their resources ensuring that the design is correct. Virtually every project uses simulation as the main verification method, relying on testbenches, constrained-random stimulus generation, and coverage as defined by the Universal Verification Methodology (UVM). Having standard testbenches and models enables easier verification reuse across projects, both within a company and across companies via a robust industry in design IP and verification IP (VIP).

PSS was defined by Accellera as a way to specify verification intent without explicitly coding a UVM testbench, UVM tests, or C/C++ tests. The idea is to specify this intent in an abstract but precise way so that a portable stimulus EDA tool can generate the files needed for verification, embedded programming, pre-silicon validation, post-silicon validation, and perhaps even some aspects of production test. The generated tests run in simulation, emulation, FPGA prototypes, and actual fabricated chips in the bringup lab.

This is a powerful concept. Automatic generation of both UVM tests and C/C++ embedded code ensures that the hardware and software aspects of the design agree. This saves a great deal of time during the validation phases. But PSS goes beyond this “horizontal” reuse to enable “vertical” reuse as well. Tests can be generated for individual IP blocks, subsystems, complete chips, and even multi-chip systems. This is a major step beyond UVM, which does not provide much assistance for reusing lower-level tests at higher levels of the design hierarchy. With PSS, it happens at the push of a button.

Adoption of Portable Stimulus

PSS was based on a number of academic and commercial projects that used some form of verification intent capture and automated test generation. By standardizing the input format and codifying the methodology, portable stimulus has emerged as an important component in chip and IP development. There are many published success stories of projects that have successfully used PSS and portable stimulus tools to save time and engineering resources while improving test coverage. The value of PSS is clear, and not many would argue against its power and capabilities.

So why isn’t every project using PSS? The simple truth is that it requires a different way of thinking about verification and validation. Any industry veteran has seen that most major advancements in chip development have required a new viewpoint and taken time to catch on. For example, both logic synthesis and constrained-random testing were being used on advanced projects for years before they went mainstream. PSS is in such a phase now; despite its many successes there are still some users who don’t truly understand it and may be nervous about trying it.

EDA history has shown that the best way to encourage adoption of new technologies is to provide automated solutions for specific problems. Many PSS observers point to the industry experience with formal verification as a relevant example. The available of pushbutton formal solutions for such challenges as clock-domain crossings (CDCs), sequential equivalence checking, and connectivity verification enabled users to get started with minimal effort. Once they saw the power of formal firsthand, they began writing their own properties and assertions to gain even more value.

Register and Sequence Specification with PSS

PSS is benefiting from an evolutionary adoption similar to formal. Writing a PSS model with the complete verification intent for an IP or chip is easier if one starts by using PSS to solve a specific problem. The specification of the registers in a design, and the sequences needed to configure and test them, is an ideal place to start. The latest release of the standard has language constructs that make it very easy to specify register sets, registers, and the fields within them. Specifying sequences is also natural with PSS, since abstract test definition is squarely within its primary function.

With a PSS model of their registers and sequences, users of the Agnisys IDesignSpec™ Suite can automatically generate many diverse types of files used by different development teams. For verification and pre-silicon validation, they generate UVM register abstraction layer (RAL) models and UVM-based tests. These include both tests based on the register types and tests that use the sequences specified in the PSS model. For pre-silicon and post-silicon validation, IDesignSpec generates C/C++ tests that run on the embedded processors in the design.

The generated tests span all the way from high-level architectural simulations to real silicon in the bringup lab. But, as per the goals of PSS, they also span from IP blocks to the complete system. Users can run UVM simulations on the register blocks standalone and then run corresponding embedded tests on a multi-chip board in the lab. There’s no recoding required; the same PSS model is used to generate all the files for all the teams. This saves time and resources not just once, but every time that the register or sequence specification changes.

Summary

The power and value of PSS has been well proven, and more chip development teams are adopting it every day. Agnisys provides an excellent way to get started, by using PSS to specify registers and sequences, followed by automated test generation. PSS support complements all the other great features in IDesignSpec, such as generation of the register RTL design and customer-ready documentation. With Agnisys, adoption of portable stimulus is fast and easy. A demonstration or evaluation license is available anytime, so don’t be shy!

To get more information about how we can help you create a functionally safe system, reach out to us here.

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Top 3 Women in Tech: A Journey of Self-Discovery

Top 3 Women in Tech: A Journey of Self-Discovery

Women have always but not least thought with discernment and perseverance while choosing a career that faced virile dominance. Three of the most prominent women in technology faced some of their worst problems in the past but they remain adamant in advancing the barriers and barriers of technology overcoming past adversities.

Their talent and unwavering will to stand out have given them an advantage in the invention process, particularly in the sphere of technology, where their influence has been felt for many years. These trailblazing women have not only surmounted obstacles but also improved the tech industry via unwavering determination and dedication. From the medical field to software startups, women have consistently shown their abilities in the workplace.

This is the list of some women who have been devoted to their journey to achieve their dreams, regardless of all obstacles and barriers.

1) Susan Wojcicki, CEO of Youtube

The CEO of YouTube, Susan Wojcicki, has been actively working in the tech industry for over twenty years. She has transcended every list of female tech CEOs and was involved in founding Google, and eventually gained her position as the first marketing manager of Google in 1999. She has managed the e-business advertising business of the company and is also responsible for Google’s original video.

As one of Google’s early recruits, the company’s twentieth employee, Susan Wojcicki, was given the responsibility of providing a home for the company’s servers. Currently, the user has a significant positive impact on the growth of both AdSense and Google Images. Born and raised in Silicon Valley she is a mother of five children She initiated the idea of YouTube acquisition in 2014 and was promoted to CEO.

Besides, she has been recognized as one of the most successful women in the tech industry, and she is famous for her powerful opinions and editorial page concerning gender inequality. Her book titled, How to Break Up the Silicon Valley Boys’ Club, can be highly recommended. She talks about the propensity of technique as being a dominating force in the current world and exemplifies this by revealing how it can cause changes that one cannot fathom. 

2) Jennifer Doudna

Doudna, a biochemist, for her great work in CRISPR gene editing, also secured a Nobel prize in December. She made efforts to modify the genomes of living organisms.

She also co-founded CRISPR disease-detecting firm Mammoth Biosciences and serves on its scientific advisory board.

She has begun five different companies applying CRISPR in ingenious ways across human therapeutics, diagnostics, sustainability, and more. Thus, Doudna works as a director for Johnson & Johnson and has dominant partnerships with Biogen, Pfizer, Roche, and Darpa.

3) Sandra L. Rivera

Sandra L. Rivera held and embraced not only one position but also many positions in the tech world. She is one of the reframe women in tech. She holds the position of executive vice president and general manager of the data center and AI group of Intel and the CEO of the Programmable Solutions Group, Intel. She guides Intel’s development of leadership data center products for a cloud-based world, including Intel Xeon and field programmable gate array (FPGA) products. Her role in steering the company’s overall artificial intelligence (AI) strategy and product roadmap.

Before guessing her current role, Rivera was Intel’s chief people officer, directing the company’s Human Resources Organization worldwide. In that leading role, she was liable for greater business results through a culture that accepts diversity and inclusion. Previously, she showcased exceptional leadership skills by overseeing the Network Platforms Group, which consisted of more than 3,000 employees. In this role, she successfully spearheaded the transformation of network infrastructure to Intel-based solutions, paving the way for innovative integration of Intel’s silicon and software portfolio to deliver enhanced customer value and satisfaction.

After Dialogic Corp was acquired by Intel in the year 2000, Rivera was posted to the company’s marketing department in the capacity of a director. Before joining Intel, Rivera was the president of Catalyst Telecom’s computer telephony segment and co-founded The CTI Authority.

CONCLUSION

These are the exemplars of women in tech who have also proven that a career in any particular field is not unattainable. Becoming one of the inspirational, influential, and reframing women in tech is viable. Women after coming into the world of tech have made this more innovative. Many more females are enlisted in the tech.  I hope this blog will be more enlightening and informative for you.

Read More:-  TOP 5 WOMEN AND THEIR ROLES IN TECH

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Field Programmable Gate Array (FPGA) Market - Forecast(2024 - 2030)

The FPGA market was valued at USD 4.79 Billion in 2017 and is anticipated to grow at a CAGR of 8.5% during 2017 and 2023. The growing demand for advanced driver-assistance systems (ADAS), the growth of IoT and reduction in time-to-market are the key driving factors for the FPGA market. Owing to benefits such as increasing the performance, early time to market, replacing glue logic, reducing number of PCB spins, and reducing number of parts of PCB, field programmable gate arrays (FPGA’s) are being used in many CPU’s. Industrial networking, industrial motor control, industrial control applications, machine vision, video surveillance make use of different families of FPGA’s.

North America is the leading market for field programmable gate arrays with U.S. leading the charge followed by Europe. North America region is forecast to have highest growth in the next few years due to growing adoption of field programmable gate arrays.

What is Field Programmable Gate Arrays?

Field Programmable Gate Arrays (FPGAs) are semiconductor devices. The lookup table (LUT) is the basic block in every FPGA. Different FPGAs use variable sized LUTs. A lookup table is logically equivalent to a RAM with the inputs being the address select lines and can have multiple outputs in order to get two Boolean functions of the same inputs thus doubling the number of configuration bits. FPGAs can be reprogrammed to desired application or functionality requirements after manufacturing. This differentiates FPGAs from Application Specific Integrated Circuits (ASICs) although they help in ASIC designing itself, which are custom manufactured for specific design tasks. 

In a single integrated circuit (IC) chip of FPGA, millions of logic gates can be incorporated. Hence, a single FPGA can replace thousands of discrete components. FPGAs are an ideal fit for many different markets due to their programmability. Ever-changing technology combined with introduction of new product portfolio is the major drivers for this industry.

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What are the major applications for Field Programmable Gate Arrays?

FPGA applications are found in Industrial, Medical, Scientific Instruments, security systems, Video & Image Processing, Wired Communications, Wireless Communications, Aerospace and Defense, Medical Electronics, Audio, Automotive, Broadcast, Consumer Electronics, Distributed Monetary Systems, Data and Computer Centers and many more verticals.

Particularly in the fields of computer hardware emulation, integrating multiple SPLDs, voice recognition, cryptography, filtering and communication encoding,  digital signal processing, bioinformatics, device controllers, software-defined radio, random logic, ASIC prototyping, medical imaging, or any other electronic processing FGPAs are implied because of their capability of being programmable according to requirement. FPGAs have gained popularity over the past decade because they are useful for a wide range of applications.

FPGAs are implied for those applications in particular where the production volume is small. For low-volume applications, the leading companies pay hardware costs per unit. The new performance dynamics and cost have extended the range of viable applications these days.

Market Research and Market Trends of Field Programmable Gate Array (FPGA) Ecosystem

FPGA As Cloud Server: IoT devices usually have limited processing power, memory size and bandwidth. The developers offer interfaces through compilers, tools, and frameworks. This creates effectiveness for the customer base and creates strong cloud products with increased efficiency which also included new machine learning techniques, Artificial Intelligence and big data analysis all in one platform. Web Service Companies are working to offer FPGAs in Elastic Compute Cloud (EC2) cloud environment. 

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Artificial Intelligence: As an order of higher magnitude performance per Watt than commercial FPGAs and (Graphical Processing Unit) GPUs in SOC search giant offers TPUs (Google’s Tensor Processing Units). AI demands for higher performance, less time, larger computation with more power proficient for deep neural networks. Deep neural network power-up the high-end devices. Google revealed that the accelerators (FGPAs) were used for the Alpha GO systems which is a computer developed by Google DeepMind that plays the board game Go.  CEA also offers an ultra-low power programmable accelerator called P-Neuro.

Photonic Networks for Hardware Accelerators: Hardware Accelerators normally need high bandwidth, low latency, and energy efficiency. The high performance computing system has critical performance which is shifted from the microprocessors to the communications infrastructure. Optical interconnects are able to address the bandwidth scalability challenges of future computing systems, by exploiting the parallel nature and capacity of wavelength division multiplexing (WDM). The multi-casted network uniquely exploits the parallelism of WDM to serve as an initial validation for architecture. Two FPGA boarded systems emulate the CPU and hardware accelerator nodes. Here FPGA transceivers implement and follow a phase-encoder header network protocol. The output of each port is individually controlled using a bitwise XNOR of port’s control signal. Optical packets are send through the network and execute switch and multicasting of two receive nodes with most reduced error

Low Power and High Data Rate FPGA: “Microsemi” FPGAs provides a non-volatile FPGA having 12.7 GB/s transceiver and lower poor consumption less than 90mW at 10 GB/s. It manufactured using a 28nm silicon-oxide-nitride-oxide-silicon nonvolatile process on standard CMOS technology. By this they address cyber security threats and deep submicron single event upsets in configuration memory on SRAM-based FPGA. These transceivers use cynical I/O gearing logic for DDR memory and LVDS. Cryptography research provides differential power analysis protection technology, an integrated physical unclonable function and 56 kilobyte of secure embedded non-volatile memory, the built-in tamper detectors parts and counter measures.

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Speeds up FPGA-in-the-loop verification: HDL Verifier is used to speed up FPGA-in-the-loop (FIL) verification. Faster communication between the FPGA board and higher clock frequency is stimulated by the FIL capabilities. This would increase the complexity of signal processing, control system algorithms and vision processing. For validation of the design in the system context simulate hardware implementation on an FPGA board. HDL Verifier automates the setup and connection of MATLAB and Simulink test environments to designs running on FPGA development boards. The R2016b has been released that allows engineers to specify a custom frequency for their FPGA system clock with clock rates up to five times faster than previously possible with FIL. This improves faster run-time. From MATLAB and Simulink is an easy way to validate hardware design within the algorithm development environment

Xilinx Unveils Revolutionary Adaptable Computing Product Category: Xilinx, Inc. which is leader in FGPAs, has recently announced a new product category which is named as Adaptive Compute Acceleration Platform (ACAP) and has the capabilities far beyond of an FPGA. An ACAP is a highly integrated multi-core heterogeneous compute platform that can be changed at the hardware level to adapt to the needs of a wide range of applications and workloads. ACAP has the capability of dynamic adaption during operation which enables it to deliver higher performance per-watt levels that is unmatched by CPUs or GPUs.

Lattice Releases Next-Generation FPGA Software for Development of Broad Market Low Power Embedded Applications: Lattice Semiconductor, launched its FPGA software recently. Lattice Radiant targeted for the development of broad market low power embedded applications. Device’s application expands significantly across various market segments including mobile, consumer, industrial, and automotive due to is rich set of features and ease-of-use, Lattice Radiant software’s support for iCE40 Ultra plus FPGAs. ICE40 Ultra Plus devices are the world’s smallest FPGAs with enhanced memory and DSPs to enable always on, distributed processing. The Lattice Radiant software is available for free download.

Who are the Major Players in market?

The companies referred in the market research report include Intel Inc, Microsemi, Lattice Semiconductor, Xilinx, Atmel, Quick Logic Corp., Red Pitaya, Mercury Computer, Nallatech Inc., Achronix Semiconductor Corporation, Acromag Inc., Actel Corp., Altera Corp.

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The report incorporates in-depth assessment of the competitive landscape, product market sizing, product benchmarking, market trends, product developments, financial analysis, strategic analysis and so on to gauge the impact forces and potential opportunities of the market. Apart from this the report also includes a study of major developments in the market such as product launches, agreements, acquisitions, collaborations, mergers and so on to comprehend the prevailing market dynamics at present and its impact during the forecast period 2017-2023.

All our reports are customizable to your company needs to a certain extent, we do provide 20 free consulting hours along with purchase of each report, and this will allow you to request any additional data to customize the report to your needs.

Key Takeaways from this Report

Evaluate market potential through analyzing growth rates (CAGR %), Volume (Units) and Value ($M) data given at country level – for product types, end use applications and by different industry verticals.

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