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Using ML Acceleration Hardware for Improved DSP Performance

Using ML Acceleration Hardware for Improved DSP Performance
by Tom Simon on 04-24-2020 at 6:00 am

nnMAX Flex Logix Tile

Some amazing hardware is being designed to accelerate AI/ML, most of which features large numbers of MAC units. Given that MAC units are like the lego blocks of digital math, they are also useful for a number of other applications. System designers are waking up to the idea of repurposing AI accelerators for DSP functions such as … Read More


Accelerating Edge Inference with Flex Logix’s InferX X1

Accelerating Edge Inference with Flex Logix’s InferX X1
by Mike Gianfagna on 04-22-2020 at 10:00 am

Screen Shot 2020 04 11 at 6.29.49 PM

For a long time, memories were the primary technology driver for process development. If you built memories, you got access to cutting-edge process information. If you built other products, this could give you a competitive edge. In many cases, FPGAs are replacing memories as the driver for advanced processes. The technology… Read More


Characteristics of an Efficient Inference Processor

Characteristics of an Efficient Inference Processor
by Tom Dillinger on 12-11-2019 at 10:00 am

The market opportunities for machine learning hardware are becoming more succinct, with the following (rather broad) categories emerging:

  1. Model training:  models are evaluated at the “hyperscale” data center;  utilizing either general purpose processors or specialized hardware, with typical numeric precision of 32-bit
Read More

Efficiency – Flex Logix’s Update on InferX™ X1 Edge Inference Co-Processor

Efficiency – Flex Logix’s Update on InferX™ X1 Edge Inference Co-Processor
by Randy Smith on 10-30-2019 at 10:00 am

Last week I attended the Linley Fall Processor Conference held in Santa Clara, CA. This blog is the first of three blogs I will be writing based on things I saw and heard at the event.

In April, Flex Logix announced its InferX X1 edge inference co-processor. At that time, Flex Logix announced that the IP would be available and that a chip,… Read More


AI Inference at the Edge – Architecture and Design

AI Inference at the Edge – Architecture and Design
by Tom Dillinger on 09-23-2019 at 10:00 am

In the old days, product architects would throw a functional block diagram “over the wall” to the design team, who would plan the physical implementation, analyze the timing of estimated critical paths, and forecast the signal switching activity on representative benchmarks.  A common reply back to the architects was, “We’veRead More


eFPGA – What a great idea! But I have no idea how I’d use it!

eFPGA – What a great idea! But I have no idea how I’d use it!
by Daniel Nenni on 08-05-2019 at 10:00 am

eFPGA stands for embedded Field Programmable Grid Arrays.  An eFPGA is a programmable device like an FPGA but rather than being sold as a completed chip it is licensed as a semiconductor IP block. ASIC designers can license this IP and embed it into their own chips adding the flexibility of programmability at an incremental cost.… Read More


Flex Logix InferX X1 Optimizes Edge Inference at Linley Processor Conference

Flex Logix InferX X1 Optimizes Edge Inference at Linley Processor Conference
by Camille Kokozaki on 04-18-2019 at 12:00 pm

Dr. Cheng Wang, Co-Founder and SVP Engineering at Flex Logix, presented the second talk in the ‘AI at the Edge’ session, at the just concluded Linley Spring Processor Conference, highlighting the InferX X1 Inference Co-Processor’s high throughout, low cost, and low power. He opened by pointing out that existing inference solutions… Read More


Real Time Object Recognition for Automotive Applications

Real Time Object Recognition for Automotive Applications
by Tom Simon on 04-12-2019 at 7:00 am

The basic principles used for neural networks have been understood for decades, what have changed to make them so successful in recent years are increased processing power, storage and training data. Layered on top of this is continued improvement in algorithms, often enabled by dramatic hardware performance improvements.… Read More


AI at the Edge

AI at the Edge
by Tom Dillinger on 12-20-2018 at 7:00 am

Frequent Semiwiki readers are well aware of the industry momentum behind machine learning applications. New opportunities are emerging at a rapid pace. High-level programming language semantics and compilers to capture and simulate neural network models have been developed to enhance developer productivity (link). Researchers… Read More


Architecture for Machine Learning Applications at the Edge

Architecture for Machine Learning Applications at the Edge
by Tom Dillinger on 10-31-2018 at 2:01 pm

Machine learning applications in data centers (or “the cloud”) have pervasively changed our environment. Advances in speech recognition and natural language understanding have enabled personal assistants to augment our daily lifestyle. Image classification and object recognition techniques enrich our social media experience,… Read More