Performance and Power Tradeoffs At 7/5nm


Semiconductor Engineering sat down to discuss power optimization with Oliver King, CTO at Moortec; João Geada, chief technologist at Ansys; Dino Toffolon, senior vice president of engineering at Synopsys; Bryan Bowyer, director of engineering at Mentor, a Siemens Business; Kiran Burli, senior director of marketing for Arm's Physical Design Group; Kam Kittrell, senior product management group d... » read more

Increase In Analog Problems


Analog and mixed signal design has always been tough, but a resent survey suggests that the industry has seen significantly increased failures in the past year because the analog circuitry within an ASIC was out of tolerance. What is causing this spike in failures? Is it just a glitch in the data, or are these problems real? The answer is complicated, and to a large extent it depends heavily... » read more

Slower Metal Bogs Down SoC Performance


Metal interconnect delays are rising, offsetting some of the gains from faster transistors at each successive process node. Older architectures were born in a time when compute time was the limiter. But with interconnects increasingly viewed as the limiter on advanced nodes, there’s an opportunity to rethink how we build systems-on-chips (SoCs). ”Interconnect delay is a fundamental tr... » read more

Searching For Power Bugs


How much power is your design meant to consume while performing a particular function? For many designs, getting this right may separate success from failure, but knowing that right number is not as easy as it sounds. Significant gaps remain between what power analysis may predict and what silicon consumes. As fast as known gaps are closed, new challenges and demands are being placed on the ... » read more

Security At The Edge


Semiconductor Engineering sat down to discuss security at the edge with Steven Woo, vice president of enterprise solutions technology and distinguished inventor at Rambus, Kris Ardis, executive director at Maxim Integrated; and Steve Roddy, vice president of Arm's Products Learning Group. What follows are excerpts of that conversation. To view part one of this discussion, click here. Part two i... » read more

Creating Domain-Specific Processors Using Custom RISC-V ISA Instructions


When System-on-Chip (SoC) developers include processors in their designs, they face choices in solving their computational challenges. Complex SoCs will usually have a variety of processor cores responsible for varied functions such as running the main application programs, communications, signal processing, security, and managing storage. Traditionally, such cores have been in distinct categor... » read more

Custom Designs, Custom Problems


Semiconductor Engineering sat down to discuss power optimization with Oliver King, CTO at Moortec; João Geada, chief technologist at Ansys; Dino Toffolon, senior vice president of engineering at Synopsys; Bryan Bowyer, director of engineering at Mentor, a Siemens Business; Kiran Burli, senior director of marketing for Arm's Physical Design Group; Kam Kittrell, senior product management group d... » read more

Integrity Problems For Edge Devices


Battery-powered edge devices need to save every picojoule of energy they can, which often means running at very low voltages. This can create signal and power integrity issues normally seen at the very latest technology nodes. But because these tend to be lower-volume, lower-cost devices, developers often cannot afford to perform the same level of analysis on these devices. Noise can come in... » read more

Is DVFS Worth The Effort?


Almost all designs have become power-aware and are being forced to consider every power saving technique, but not all of them are yielding the expected results. Moreover, they can add significant complexity into designs, increasing the time it takes to get to tapeout and boosting up the cost. Dynamic voltage and frequency scaling (DVFS) is one such power and energy saving technique now being... » read more

Compiling And Optimizing Neural Nets


Edge inference engines often run a slimmed-down real-time engine that interprets a neural-network model, invoking kernels as it goes. But higher performance can be achieved by pre-compiling the model and running it directly, with no interpretation — as long as the use case permits it. At compile time, optimizations are possible that wouldn’t be available if interpreting. By quantizing au... » read more

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