tag: ResNet

Embrace The New!
By Steve Roddy - 14 Mar, 2024 - Comments: 0

The ResNet family of machine learning algorithms was introduced to the AI world in 2015. A slew of variations was rapidly discovered that at the time pushed the accuracy of ResNets close to the 80% threshold (78.57% Top 1 accuracy for ResNet-152 on ImageNet). This state-of-the-art performance at the time, coupled with the rather simple operator structure that was readily amenable to hardware ac... » read more

Will Markets For ML Models Materialize?
By Bryon Moyer - 02 Dec, 2021 - Comments: 0

Developers are spending increasing amounts of time and effort in creating machine-learning (ML) models for use in a wide variety of applications. While this will continue as the market matures, at some point some of these efforts might be seen as reinventing models over and over. Will developers of successful models ever have a marketplace in which they can sell those models as IP to other d... » read more

Customized Micro-Benchmarks For HW/SW Performance
By Ed Sperling - 23 Mar, 2021 - Comments: 0

Raw performance used to be the main focus of benchmarks, but they may have outlived their usefulness for many applications. Dana McCarty, vice president of sales and marketing for AI Inference Products at Flex Logix, talks about why companies need to develop and utilize their own specific models to accurately gauge hardware and software performance, which can be slowed by bottlenecks in I/O and... » read more

Edge-Inference Architectures Proliferate
By Bryon Moyer - 04 Feb, 2021 - Comments: 0

First part of two parts. The second part will dive into basic architectural characteristics. The last year has seen a vast array of announcements of new machine-learning (ML) architectures for edge inference. Unburdened by the need to support training, but tasked with low latency, the devices exhibit extremely varied approaches to ML inference. “Architecture is changing both in the comp... » read more

Fast, Low-Power Inferencing
By Russell Klein - 10 Dec, 2020 - Comments: 1

Power and performance are often thought of as opposing goals, opposite sides of the same coin if you will. A system can be run really fast, but it will burn a lot of power. Ease up on the accelerator and power consumption goes down, but so does performance. Optimizing for both power and performance is challenging. Inferencing algorithms for Convolutional Neural Networks (CNN) are compute int... » read more

The Murky World Of AI Benchmarks
By Ann Mutschler - 30 Apr, 2020 - Comments: 0

AI startup companies have been emerging at breakneck speed for the past few years, all the while touting TOPS benchmark data. But what does it really mean and does a TOPS number apply across every application? Answer: It depends on a variety of factors. Historically, every class of design has used some kind of standard benchmark for both product development and positioning. For example, SPEC... » read more

Inferencing At The Edge
By Ed Sperling - 04 Jun, 2019 - Comments: 0

Geoff Tate, CEO of Flex Logix, talks about the challenges of power and performance at the edge, why this market is so important from a business and technology standpoint, and what factors need to be balanced. » read more

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