AI is being designed into a growing number of chips and systems at the edge, where it is being used to speed up the processing of massive amounts of data, and to reduce power by partitioning and prioritization. That, in turn, allows systems to act upon that data more rapidly.
Flex Logix Technologies announced that it has partnered with Intrinsic ID to ensure that any device using its eFPGA remains secure and can’t be modified maliciously, whether through physical attacks or remote hacking.
FLEX LOGIX COLLABORATING WITH MICROSOFT TO HELP BUILD SECURE STATE-OF-THE-ART CHIPS FOR US DEPARTMENT OF DEFENSE (DOD)
Flex Logix(R) Technologies, Inc., the leading supplier of embedded FPGA (eFPGA) IP, architecture and software, announced today that it has been selected to be part of a team of microelectronic industry leaders, led by Microsoft, to build a chip development platform with the utmost regard for security as demonstrated by the DoD RAMP Project. Flex Logix was chosen for its leading embedded (eFPGA) technology that enables chips to be reconfigurable after tape-out, allowing companies to adapt to new requirements, changing standards and protocols as needed.
Experience at NVIDIA and Xilinx will help strengthen Flex Logix’s product roadmap and accelerate its next phase of growth
FLEX LOGIX AND CEVA ANNOUNCE FIRST WORKING SILICON OF A DSP WITH EMBEDDED FPGA TO ALLOW A FLEXIBLE/CHANGEABLE ISA
Flex Logix® Technologies, Inc. and CEVA, Inc. have announced today the world's first successful silicon implementation using Flex Logix's EFLX® embedded FPGA (eFPGA) connected to a CEVA-X2 DSP instruction extension interface.
Flex Logix Launches EasyVision - Turnkey AI/ML Solution With Ready-to-Use Models and AI Acceleration Hardware
MOUNTAIN VIEW, Calif., June 6, 2022 /PRNewswire/ -- Flex Logix® Technologies, Inc., supplier of fast and efficient edge AI inference accelerators, announced today the availability of EasyVision Platforms designed to help customers get to market quickly with edge computer vision products for a wide range of markets such as robotic vision, industrial, security, and retail analytics. EasyVision features the industry's most efficient edge AI accelerator, the InferX™, along with ready-to-use models that are trained to perform the most common object detection capabilities such as hard-hat detection, people counting, face mask detection and license plate recognition.
Silicon Catalyst, the world’s only incubator focused exclusively on accelerating semiconductor solutions, is pleased to announce that Flex Logix® has joined as the newest member of its In-Kind Partner program (IKP). Portfolio companies in the Silicon Catalyst Incubator will have access to Flex Logix’s innovative embedded FPGA (eFPGA) IP and software, enabling silicon reconfigurability for use in their chip designs.
The availability of AI models optimized for the Flex Logix InferX accelerator enables edge device manufacturers to get to market quickly, reliably and affordably.
AI at the edge is very different than AI in the cloud. Salvador Alvarez, solution architect director at Flex Logix, talks about why a specialized inferencing chip with built-in programmability is more efficient and scalable than a general-purpose processor, why high-performance models are essential for getting accurate real-time results, and how low power and ambient temperatures can affect the performance and life expectancy of these devices.
We caught up with Sam to discuss what Flex Logix does, what the InferX platform is, how both the company and the platform differ from the competition, how easy it is to port models to the InferX platform, and more.
FLEX LOGIX APPOINTS CHRIS PASSIER AS VICE PRESIDENT, PLATFORM SOFTWARE AND VANCOUVER, CANADA SITE EXECUTIVE
MOUNTAIN VIEW, Calif., April 18, 2022 /PRNewswire/ -- Flex Logix® Technologies, Inc., supplier of fast and efficient edge AI inference accelerators and the leading supplier of eFPGA IP, today announced the appointment of Chris Passier as Vice President for Platform Software and Vancouver Canada Site Executive. Chris brings a wealth of experience to Flex Logix having been in senior software leadership roles at Dell Networking, Ericsson Telecom and Rockport Networks.
Before Covid-induced supply chain issues affected semiconductor availability and lead times, concerns about counterfeit parts and trusted supply chains were becoming the subject of many articles and discussions...
Flex Logix® Technologies, Inc., the leading supplier of embedded FPGA (eFPGA) IP, architecture and software, announced today that it has reached a significant milestone of signing licenses to develop more than 32 ASICs/SoCs integrating EFLX, with nearly half already working in silicon.
MOUNTAIN VIEW, Calif., March 29, 2022 /PRNewswire/ -- Flex Logix® Technologies, Inc., supplier of the most-efficient AI edge inference accelerator and the leading supplier of eFPGA IP, today announced production availability of its InferX™ X1M boards. At roughly the size of a stick of gum, the new InferX X1M boards pack high performance inference capabilities into a low-power M.2 form factor for space and power constrained applications such as robotic vision, industrial, security, and retail analytics.
Every type of edge AI has three hard and fast technical requirements: low power, small form factor, and high performance. Of course, what constitutes “small,” “power efficient,” or “high performance” varies by use case and can describe everything from small microcontrollers to edge servers, but usually you must sacrifice at least one to get the others. However, one solution that can address everything from edge clouds to endpoints without sacrifice is the FPGA.
TO INCLUDE ANY FLEX LOGIX TECHNOLOGY FOR RESEARCH AND CHIP PROTOTYPING IN ALL AVAILABLE PROCESSES INCLUDING RADHARD Enables any US Government-funded research programs and activities to use reconfigurable computing IP for no license fees
FPGA has become strategic technology. It is strategically important to two very big, high-growth applications: Cloud data centers and Communications systems including 5G, and acquisitions of FPGA companies confirm this. Why? Because of Parallel programming, but FPGAs have some concerns. This presentation will talk about how embedding FPGAs (eFPGA) can change the use case for FPGA and the way software is controlled.
Machine vision is rapidly becoming a key enabling technology for digitalization and automation in automotive, healthcare, manufacturing, retail, smart buildings, smart cities, transportation, and logistics. According to ABI Research, a global technology intelligence firm, the total revenue of machine vision technology in the seven major markets is expected to reach US$36 billion by 2027, up from US$21.4 billion in 2022. This growth translates to a CAGR of 11%.
Dozens of startups continue to get tens of millions in venture funding to make chips for AI in mobile and other embedded computing uses. The race shows no sign of slowing down.
Co-Founder Cheng Wang promoted to SVP and CTO; VP Software and VP People strengthen existing management team as company enters its next phase of growth and expansion.
Artificial intelligence chips, or AI chips, are being increasingly used for autonomous processes, smart devices, telecommunications, and much more. According to McKinsey & Company, it’s estimated that by 2025, AI-related semiconductors could reach $67 billion in annual sales - approximately 20% of computer chip demand.
The X1 was specified to be a lean, high performance edge accelerator for AI inference processing incorporating Flex Logix’ proprietary tensor processor, PCIe, DDR, memory, and a NoC. And we ran into an issue...
eFPGA Market has come a long ways over the years. Find out where its going in 2022.
Embedded FPGA (eFPGA) is the next big market for semiconductor IP. It can be used on almost every kind of digital chip and has a significant software value add as well—much like the market for embedded processors. When it comes to chip design, eFPGA provides competitive advantages that can add up to millions of dollars in savings and flexibility that wasn’t possible until now.
Consider these 6 factors when selecting an AI accelerator for your medical device.
It’s an exciting time to be a part of the rapidly growing AI industry, particularly in the field of inference. Once relegated simply to high-end and outrageously expensive computing systems, AI inference has been marching towards the edge at super-fast speeds. Today, customers in a wide range of industries – from medical, industrial, robotics, security, retail and imaging – are either evaluating or actually designing AI inference capabilities into their products and applications.
Why it’s so important to match the AI task to the right type of chip. Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train a model to enable the machine to learn how to perform a task. ML training is highly iterative with each new piece of training data generating trillions of operations.
An edge inference accelerator developed by Flexlogix has a 4k MAC dynamic tensor processor array and is optimised for Mpixel image processing models in medical, surveillance and IoT applications.
Flex Logix is a reconfigurable computing company that provides AI Inference and eFPGA solutions that are based on software, silicon, and systems. The company is headquartered in Mountain View, CA. It is one of the top Edge AI companies that has recently announced the production availability of its InferX X1P1 accelerator board. The InferX X1P1 board offers the most efficient AI inference acceleration for edge workloads such as Yolov3.
Membership will help support Flex Logix's rapid growth in the edge vision market with its inference accelerator chips and boards.
Bringing commercial innovations in chip design to national security.
Flex Logix Accelerates Growth With New Office In Austin; Prepares For Global Expansion Of Its Edge AI Inference Product Line The Company is Actively Hiring Both Software and Hardware Engineers
Watch the video to explore how a company with analog or MCU expertise combined with eFPGA saves their end customer power, cost and increase flexibility.
The advent of machine learning techniques has benefited greatly from the use of acceleration technology such as GPUs, TPUs and FPGAs. Indeed, without the use of acceleration technology, it’s likely that machine learning would have remained in the province of academia and not had the impact that it is having in our world today.
Embedded FPGA Revolutionizes Chip Development by Enabling Organizations such as Sandia to Reconfigure RTL at any Point During the Design Process