tag: AI accelerator

Image Processing For Vision AI
By Renesas - 23 Feb, 2022 - Comments: 0

Recent years have seen an increasing need for Vision AI applications using AI to enable real-time image recognition. Vision AI, which substitutes AI for human visual recognition, requires optimal image processing. Renesas has released RZ/V2M as mid-class, and RZ/V2L as an entry class, Vision AI microprocessors (MPUs). Both products are equipped with DRP-AI which is Dynamically Reconfigurable Pr... » read more

eFPGA Saved Us Millions of Dollars. It Can Do the Same for You
By Andy Jaros - 03 Feb, 2022 - Comments: 0

For those of you who follow Flex Logix, you already know that we have an IP business, EFLX eFGPA, and an edge inferencing co-processor chip and board business, InferX. InferX came about because we had many customers ask if they can run AI/ML algorithms in EFLX. The answer was and still is, of course you can – EFLX is an FPGA fabric similar to what FPGA chips use. Our co-founder, Cheng Wang, t... » read more

Flexible USB4-Based Interface IP Solution For AI At The Edge
By Synopsys - 21 Dec, 2021 - Comments: 0

Consumers have become accustomed to smart devices that are powered by advances in artificial intelligence (AI). To expand the devices’ total addressable market, innovative device designers build edge AI accelerators and edge AI SoCs that support multiple use cases and integration options. This white paper describes a flexible USB4-based IP solution for edge AI accelerators and SoCs. The IP so... » read more

Getting Better Edge Performance & Efficiency From Acceleration-Aware ML Model Design
By Vlad Bronstein - 04 Nov, 2021 - Comments: 0

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. Clearly, machine learning has become an important tool for solving... » read more

Challenges In Developing A New Inferencing Chip
By Ed Sperling - 01 Jul, 2021 - Comments: 0

Cheng Wang, co-founder and senior vice president of software and engineering at Flex Logix, sat down with Semiconductor Engineering to explain the process of bringing an inferencing accelerator chip to market, from bring-up, programming and partitioning to tradeoffs involving speed and customization.   SE: Edge inferencing chips are just starting to come to market. What challenges di... » read more

Xilinx AI Engines And Their Applications
By Xilinx - 31 Mar, 2021 - Comments: 0

This white paper explores the architecture, applications, and benefits of using Xilinx's new AI Engine for compute intensive applications like 5G cellular and machine learning DNN/CNN. 5G requires between five to 10 times higher compute density when compared with prior generations; AI Engines have been optimized for DSP, meeting both the throughput and compute requirements to deliver the hig... » read more

Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud
By Technical Paper Link - 06 Mar, 2021 - Comments: 0

SOURCE: Shulin Zeng, Guohao Dai, Hanbo Sun, Kai Zhong, Guangjun Ge, Kaiyuan Guo, Yu Wang, Huazhong Yang(Tsinghua University, Beijing, China).  Published on arXiv:2003.12101 [cs.DC])   ABSTRACT: "FPGAs have shown great potential in providing low-latency and energy-efficient solutions for deep neural network (DNN) inference applications. Currently, the majority of FPGA-based DNN accel... » read more

Virtualizing FPGAs For Multiple Cloud Users
By Song Yao - 04 Mar, 2021 - Comments: 0

Cloud computing has become the new computing paradigm. For cloud computing, virtualization is necessary to enable isolation between users, high flexibility and scalability, high security, and maximized utilization of hardware resources. Since 2017, because of the advantages of programmability, low latency, and high energy efficiency, FPGA has been widely adopted into cloud computing. Amazon ... » read more

Power/Performance Bits: Feb. 23
By Jesse Allen - 23 Feb, 2021 - Comments: 0

Photonic AI accelerator There are now many processors and accelerators focused on speeding up neural network performance, but researchers at the University of Münster, University of Oxford, Swiss Federal Institute of Technology Lausanne (EPFL), IBM Research Europe, and University of Exeter say AI processing could happen even faster with the use of photonic tensor processors that can handle mu... » read more

Startup Funding: November 2020
By Jesse Allen - 02 Dec, 2020 - Comments: 0

Numerous chipmakers pulled in funding in November 2020, with investors putting money into interconnects, memories, AI hardware, and quantum computing. Launching from stealth was a startup aiming to combine AI and 5G. Autonomous delivery did well, too, with one company raising a massive $500M. This month, we take a look at 28 companies that raised a collective $1.1B. Semi & design Connec... » read more

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