The conventional thinking about programmable solutions such as FPGAs is that you have to be willing to make a lot of trade-offs for their flexibility. This has certainly been the case in many instances. Even just getting data across the chip can eat up valuable routing resources and add a lot of overhead. These problems are exacerbated… Read More
New Generation of FPGA Based Distributed Accelerator Cards Offer High Performance and Adaptability
We have learned from nature that two characteristics are helpful for success, diversity and adaptability. The same has been shown to be true for computing systems. Things have come a long way from when CPU centric computing was the only choice. Much heavy lifting these days is done by GPUs, ASICs, and FPGAs, with CPUs in a support … Read More
Achronix Announces New Accelerator Card at Linley Fall Processor Conference – VectorPath
This blog is my second blog from this year’s Linley Fall Processor Conference. The first two blogs focused on edge inference solutions. Achronix’s discussion was much broader than just AI/ML; it was about where FPGA’s have been going and culminated with a product announcement preview. I’ll get to the announcement in a moment, … Read More
Design Perspectives on Intermittent Faults
Bugs are an inescapable reality in any but the most trivial designs and usually trace back to very deterministic causes – a misunderstanding of the intended spec or an incompletely thought-through implementation of some feature, either way leading to reliably reproducible failure under the right circumstances. You run diagnostics,… Read More
Acceleration in a Heterogenous Compute Environment
Heterogenous compute isn’t a new concept. We’ve had it in phones and datacenters for quite a while – CPUs complemented by GPUs, DSPs and perhaps other specialized processors. But each of these compute engines has a very specific role, each driven by its own software (or training in the case of AI accelerators). You write software… Read More
Xilinx on ANSYS Elastic Compute for Timing and EM/IR
I’m a fan of getting customer reality checks on advanced design technologies. This is not so much because vendors put the best possible spin on their product capabilities; of course they do (within reason), as does every other company aiming to stay in business. But application by customers on real designs often shows lower performance,… Read More
Tortuga Webinar: Ensuring System Level Security Through HW/SW Verification
We all know (I hope) that security is important so we’re willing to invest time and money in this area but there are a couple of problems. First there’s no point in making your design secure if it’s not competitive and making it competitive is hard enough, so the great majority of resource and investment is going to go into that objective.… Read More
An AI Accelerator Ecosystem For High-Level Synthesis
AI accelerators as engines for object or speech recognition (among many possibilities), are becoming increasingly popular for inference in mobile and power-constrained applications. Today much of this inferencing runs largely in software on CPUs or GPUs thanks to the sheer size of the smartphone market, but that will shift… Read More
An evolution in FPGAs
Why does it seem like current FPGA devices work very much like the original telephone systems with exchanges where workers connected calls using cords and plugs? Achronix thinks it is now time to jettison Switch Blocks and adopt a new approach. Their motivation is to improve the suitability of FPGAs to machine learning applications,… Read More
Flex Logix InferX X1 Optimizes Edge Inference at Linley Processor Conference
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
Podcast EP267: The Broad Impact Weebit Nano’s ReRAM is having with Coby Hanoch