tag: GPNPU

AI Moves Out Of The Cloud And Onto The Edge
By Lee Vick - 11 Dec, 2025 - Comments: 0

The impact of AI to date, in the cloud, is undisputed, but the question we must answer going forward is whether we can only expect more of the same or whether there is a fundamental shift looming that will change everything. Today, we will explore historical data to find patterns repeated through the ages to help us see what I will attempt to prove is imminent. A brief history of time… keepi... » read more

Vision Language Models Come Rushing In
By Steve Roddy - 17 Feb, 2025 - Comments: 0

Just when you thought the pace of change of AI models couldn’t get any faster, it accelerates yet again. In the popular news media, the introduction of DeepSeek in January 2025 created a moment that captured headlines in every newspaper and website heralding comparisons to the Sputnik moment of 1957. But rapid change is also happening in many quarters that are hidden from view of the Chat-App... » read more

ConvNext Runs 28X Faster Than Fallback
By Steve Roddy - 22 Jul, 2024 - Comments: 0

Two months ago in our blog we highlighted the fallacy of using a conventional NPU accelerator paired with a DSP or CPU for “fallback” operations. (Fallback Fails Spectacularly, May 2024). In that blog we calculated what the expected performance would be for a system with a DSP needing to perform the new operations found in one of today’s leading new ML networks – ConvNext. The result wa... » read more

KANs Explode!
By Steve Roddy - 13 Jun, 2024 - Comments: 0

In late April 2024, a novel AI research paper was published by researchers from MIT and CalTech proposing a fundamentally new approach to machine learning networks – the Kolmogorov Arnold Network – or KAN. In the six weeks since its publication, the AI research field is ablaze with excitement and speculation that KANs might be a breakthrough that dramatically alters the trajectory of AI mod... » read more

Fallback Fails Spectacularly
By Steve Roddy - 16 May, 2024 - Comments: 0

Conventional AI/ML inference silicon designs employ a dedicated, hardwired matrix engine – typically called an “NPU” – paired with a legacy programmable processor – either a CPU, or DSP, or GPU. The common theory behind these two-core (or even three core) architectures is that most of the matrix-heavy machine learning workload runs on the dedicated accelerator for maximum efficienc... » read more

Hybrid Architecture Blends Best Of Both Worlds
By Steve Roddy - 11 Apr, 2024 - Comments: 0

Quadric chose the brand name Chimera to describe the company’s novel general purpose neural processing unit (GPNPU) architecture. According to the online Oxford dictionary, in biology a chimera is “an organism containing a mixture of genetically different tissues (or DNA).” Quadric made that naming choice to reflect the fact that its Chimera GPNPU has characteristics of both conventiona... » read more

Compiler-Driven Performance Boosts For GPNPUs
By Steve Roddy - 10 Aug, 2023 - Comments: 0

The GNU C Compiler – GCC – was first released in 1987. 36 years ago. Several version streams are still actively being developed and enhanced, with GCC13 being the most advanced, and a GCC v10.5 released in early July this year. You might think that with 36 years of refinement by thousands of contributors that penultimate performance has been achieved. All that could be discovered has bee... » read more

A Bridge From Mars To Venus
By Steve Roddy - 20 Jul, 2023 - Comments: 0

In a now-famous 1992 pop psychology book titled "Men Are from Mars, Women Are from Venus," author John Gray posited that most relationship troubles in couples stem from fundamental differences in socialization patterns between men and women. The analogy that the two partners came from different planets was used to describe how two people could perceive issues in completely different and sometim... » read more

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