The Murky World Of AI Benchmarks


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

Power Becomes Bigger Concern For Embedded Processors


Power is emerging as the dominant concern for embedded processors even in applications where performance is billed as the top design criteria. This is happening regardless of the end application or the process node. In some high-performance applications, power density and thermal dissipation can limit how fast a processor can run. This is compounded by concerns about cyber and physical secur... » read more

Blog Review: Feb. 12


Complexity is growing by process node, by end application, and in each design. The latest crop of blogs points to just how many dependencies and uncertainties exist today, and what the entire supply chain is doing about them. Mentor's Shivani Joshi digs into various types of constraints in PCBs. Cadence's Neelabh Singh examines the complexities of verifying a lane adapter state machine in... » read more

Software In Inference Accelerators


Geoff Tate, CEO of Flex Logix, talks about the importance of hardware-software co-design for inference accelerators, how that affects performance and power, and what new approaches chipmakers are taking to bring AI chips to market. » read more

Tradeoffs In Embedded Vision SoCs


Gordon Cooper, product marketing manager for embedded vision processors at Synopsys, talks with Semiconductor Engineering about the need for more performance in these devices, how that impacts power, and what can be done to optimize both prior to manufacturing. » read more

Making Sense Of ML Metrics


Steve Roddy, vice president of products for Arm’s Machine Learning Group, talks with Semiconductor Engineering about what different metrics actually mean, and why they can vary by individual applications and use cases. » read more

TOPS, Memory, Throughput And Inference Efficiency


Dozens of companies have or are developing IP and chips for Neural Network Inference. Almost every AI company gives TOPS but little other information. What is TOPS? It means Trillions or Tera Operations per Second. It is primarily a measure of the maximum achievable throughput but not a measure of actual throughput. Most operations are MACs (multiply/accumulates), so TOPS = (number of MAC... » read more

Benchmarks For The Edge


Geoff Tate, CEO of Flex Logix, talks about benchmarking in edge devices, particularly for convolutional neural networks. https://youtu.be/-beVEpKAM4M » read more

Lies, Damn Lies, And TOPS/Watt


There are almost a dozen vendors promoting inferencing IP, but none of them gives even a ResNet-50 benchmark. The only information they state typically is TOPS (Tera-Operations/Second) and TOPS/Watt. These two indicators of performance and power efficiency are almost useless by themselves. So what, exactly, does X TOPS really tell you about performance for your application? When a vendor ... » read more