Semifore is Supplying Pain Relief for Some World-Changing Applications

Semifore is Supplying Pain Relief for Some World-Changing Applications
by Mike Gianfagna on 09-23-2022 at 8:00 am

Semifore is Supplying Pain Relief for Some World Changing Applications

In a recent post, I discussed how Samtec is fueling the AI revolution. In that post, I talked about how smart everything seems to be everywhere, changing the way we work, the way we think about our health and ultimately improving life on the planet. These are lofty statements, but the evidence is growing that the newest wave of applications… Read More


High Efficiency Edge Vision Processing Based on Dynamically Reconfigurable TPU Technology

High Efficiency Edge Vision Processing Based on Dynamically Reconfigurable TPU Technology
by Kalar Rajendiran on 05-02-2022 at 6:00 am

Fast model evolution Flexibility is key

While many tough problems relating to computing have been solved over the years, vision processing is still challenging in many ways. Cheng Wang, Co-Founder and CTO of FlexLogix Technologies gave a talk on the topic of edge vision processing at Linley’s Spring 2022 conference. During that talk he references how Gerald Sussman… Read More


Flex Logix Expands Its eFPGA Footprint with a Low Power Comms Design Win from OpenFive

Flex Logix Expands Its eFPGA Footprint with a Low Power Comms Design Win from OpenFive
by Mike Gianfagna on 12-21-2020 at 10:00 am

Flex Logix Expands Its eFPGA Footprint with a Low Power Comms Design Win from OpenFive

Embedded FPGA use is on the rise. The programmability offered by this kind of IP finds many applications in complex SoCs. There was a recent announcement that OpenFive had licensed Flex Logix’s eFPGA to develop a low power communications SoC. The part required a large eFPGA. The news was reported on SemiWiki here. This announcement… 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
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Embedded FPGA IP as a Post-Silicon Debugger

Embedded FPGA IP as a Post-Silicon Debugger
by Tom Dillinger on 09-08-2017 at 12:00 pm

The hardware functionality of a complex SoC is difficult to verify. Embedded software developed for a complex, multi-core SoC is extremely difficult to verify. An RTOS may need to be ported and validated. Application software needs to be developed, and optimized for performance. Sophisticated methodologies are employed to… Read More