tag: Quadric

No Fooling With Voxel Pooling
By Steve Roddy - 13 Mar, 2025 - Comments: 0

A variety of new and complicated transformer models have emerged in the past 18 to 24 months as new “must have” networks in advanced automotive use cases. These novel architectures often introduce new network operators or novel ways of combining tensors – often from different types of sensors – in ways to enhance detection and recognition of objects in L3 / L4 / L5 ADAS and autonomous d... » 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

Normalization Keeps AI Numbers In Check
By Bryon Moyer - 13 Feb, 2025 - Comments: 0

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model processes its inputs, those calculations may go astray. Normalization is a process that can keep data in bounds, improving both training and inference. Foregoing normalization can result in at... » read more

Chip Industry Week In Review
By The SE Staff - 31 Jan, 2025 - Comments: 0

Chinese startup DeepSeek rattled the tech world and U.S. stock market with claims it spent just $5.6 million on compute power for its AI model compared to its billion-dollar rivals in the U.S. The announcement raised questions about U.S. investment strategies in AI infrastructure and led to an initial $600 billion selloff of NVIDIA stock. Since its launch, DeepSeek reportedly was hit by malicio... » read more

MACs Are Not Enough: Why “Offload” Fails
By Steve Roddy - 16 Jan, 2025 - Comments: 0

For the past half-decade, countless chip designers have approached the challenges of on-device machine learning inference with the simple idea of building a “MAC accelerator” – an array of high-performance multiply-accumulate circuits – paired with a legacy programmable core to tackle the ML inference compute problem. There are literally dozens of lookalike architectures in the market t... » read more

2025: So Many Possibilities
By Brian Bailey - 16 Jan, 2025 - Comments: 0

The stage is set for a year of innovation in the chip industry, unlike anything seen for decades, but what makes this period of advancement truly unique is the need to focus on physics and real design skills. Planar scaling of SoCs enabled design and verification tools and methodologies to mature on a relatively linear path, but the last few years have created an environment for more radical... » read more

What’s The Best Way To Sell An Inference Engine?
By Bryon Moyer - 16 Jan, 2025 - Comments: 0

The burgeoning AI market has seen innumerable startups funded on the strength of their ideas about building faster, lower-power, and/or lower-cost AI inference engines. Part of the go-to-market dynamic has involved deciding whether to offer a chip or IP — with some newcomers pivoting between chip and IP implementations of their ideas. The fact that some companies choose to sell chips while... » read more

Startup Challenges In A Changing EDA World
By Brian Bailey - 13 Jan, 2025 - Comments: 0

The Electronic Design Automation (EDA) industry is a mature industry, but it's also one that is constantly changing. Each process node and packaging technology advancement places new demands and constraints on existing tools. In addition, changing design problems and paradigms transform how design teams operate, and the goals they target. For a relatively small industry, EDA requires a dispr... » read more

Is In-Memory Compute Still Alive?
By Bryon Moyer - 12 Dec, 2024 - Comments: 1

In-memory computing (IMC) has had a rough go, with the most visible attempt at commercialization falling short. And while some companies have pivoted to digital and others have outright abandoned the technology, developers are still trying to make analog IMC a success. There is disagreement regarding the benefits of IMC (also called compute-in-memory, or CIM). Some say it’s all about reduc... » read more

To (B)atch Or Not To (B)atch?
By Steve Roddy - 18 Nov, 2024 - Comments: 0

When evaluating benchmark results for AI/ML processing solutions, it is very helpful to remember Shakespeare’s Hamlet, and the famous line: “To be, or not to be.” Except in this case the “B” stands for Batched. Batch size matters There are two different ways in which a machine learning inference workload can be used in a system. A particular ML graph can be used one time, preced... » read more

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