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
FPGA Landscape Update 2019
In 2015 Intel acquired Altera for $16.7B changing one of the most heated rivalries (Xilinx vs Altera) the fabless semiconductor ecosystem has ever seen. Prior to the acquisition the FPGA market was fairly evenly split between Xilinx and Altera with Lattice and Actel playing to market niches in the shadows. There were also two FPGA… Read More
ARM, NXP Share Usage, Challenges at Synopsys Lunch
Synopsys runs a “Industry verifies with Synopsys” lunch at each DVCon, which isn’t as cheesy as the title might suggest. The bulk of the lunch covers user presentations on their use of Synopsys tools which I find informative and quite open, sharing problems as much as successes. This year, Eamonn Quiqley, FPGA engineering manager… Read More
Segmenting the Machine-Learning Hardware Market
One of the great pleasures in what I do is to work with people who are working with people in some of the hottest design areas today. A second-level indirect to be sure but that gives me the luxury of taking a broad view. A recent discussion I had with Kurt Shuler (VP Marketing at Arteris IP) is in this class. As a conscientious marketing… Read More
Why NA is Not Relevant to Resolution in EUV Lithography