tag: Quadric

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

New AI Data Types Emerge
By Bryon Moyer - 14 Nov, 2024 - Comments: 0

AI is all about data, and the representation of the data matters strongly. But after focusing primarily on 8-bit integers and 32‑bit floating-point numbers, the industry is now looking at new formats. There is no single best type for every situation, because the choice depends on the type of AI model, whether accuracy, performance, or power is prioritized, and where the computing happens, ... » read more

AI Drives IC Design Shifts At The Edge
By Adam Kovac and Ed Sperling - 07 Nov, 2024 - Comments: 0

The increasing adoption of AI in edge devices, coupled with a growing demand for new features, is forcing chipmakers to rethink when and where data gets processed, what kind of processors to use, and how to build enough flexibility into systems to span multiple markets. Unlike in the cloud, where the solution generally involves nearly unlimited resources, computing at the edge has sharp cons... » read more

Chip Industry Week In Review
By The SE Staff - 01 Nov, 2024 - Comments: 0

Siemens announced plans to acquire Altair Engineering, a provider of industrial simulation and analysis, data science, and high-performance computing (HPC) software, for about $10 billion. Altair's software will become part of Siemens' Xcelerator portfolio and provide a boost to physics-based digital twins. Onto Innovation bought Lumina Instruments, a San Jose, California-based maker of lase... » read more

In Memory, At Memory, Near Memory: What Would Goldilocks Choose?
By Steve Roddy - 17 Oct, 2024 - Comments: 0

The children’s fairy tale of ‘Goldilocks and the Three Bears’ describes the adventures of Goldi as she tries to choose among three choices for bedding, chairs, and bowls of porridge. One meal is “too hot,” the other “too cold,” and finally one is “just right.” If Goldi were faced with making architecture choices for AI processing in modern edge/device SoCs, she would also face... » read more

Mass Customization For AI Inference
By Ann Mutschler - 17 Oct, 2024 - Comments: 0

Rising complexity in AI models and an explosion in the number and variety of networks is leaving chipmakers torn between fixed-function acceleration and more programmable accelerators, and creating some novel approaches that include some of both. By all accounts, a general-purpose approach to AI processing is not meeting the grade. General-purpose processors are exactly that. They're not des... » read more

Using AI To Glue Disparate IC Ecosystem Data
By Ed Sperling and Ann Mutschler - 26 Sep, 2024 - Comments: 0

AI holds the potential to change how companies interact throughout the global semiconductor ecosystem, gluing together different data types and processes that can be shared between companies that in the past had little or no direct connections. Chipmakers always have used abstraction layers to see the bigger picture of how the various components of a chip go together, allowing them to pinpoi... » read more

Can You Rely Upon Your NPU Vendor To Be Your Customers’ Data Science Team?
By Steve Roddy - 12 Sep, 2024 - Comments: 0

The biggest mistake a chip design team can make in evaluating AI acceleration options for a new SoC is to rely entirely upon spreadsheets of performance numbers from the NPU vendor without going through the exercise of porting one or more new machine learning networks themselves using the vendor toolsets. Why is this a huge red flag? Most NPU vendors tell prospective customers that (1) the v... » read more

Balancing Programmability And Performance In Cars
By Ann Mutschler - 05 Sep, 2024 - Comments: 0

The rate of change in the automotive industry is accelerating with the shift toward software-defined vehicles and ongoing advancements in algorithms and chip architectures. The challenge now is to figure out the best way to prevent rapid obsolescence, improve safety, and keep the cost of these changes to a minimum. Today, updatable automotive hardware is typically achieved through FPGAs, but... » read more

AI’s Role In Chip Design Widens, Drawing In New Startups
By Karen Heyman - 29 Aug, 2024 - Comments: 0

Using AI in EDA is reinvigorating the whole tools industry, prompting established players to upgrade their tool offerings with AI/ML features, while drawing in startups trying to carve out differentiated approaches to fill unaddressed gaps with new tools and methodologies. Today’s new generation of entrepreneurs is comprised of both young post-grads with innovative ideas and industry veter... » read more

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