Growth Spurred By Negatives


The success and health of the semiconductor industry is driven by the insatiable appetite for increasingly complex devices that impact every aspect of our lives. The number of design starts for the chips used in those devices drives the EDA industry. But at no point in history have there been as many market segments driving innovation as there are today. Moreover, there is no indication this... » read more

Is Programmable Overhead Worth The Cost?


Programmability has fueled the growth of most semiconductor products, but how much does it actually cost? And is that cost worth it? The answer is more complicated than a simple efficiency formula. It can vary by application, by maturity of technology in a particular market, and in the context of much larger systems. What's considered important for one design may be very different for anothe... » read more

The High But Often Unnecessary Cost Of Coherence


Cache coherency, a common technique for improving performance in chips, is becoming less useful as general-purpose processors are supplemented with, and sometimes supplanted by, highly specialized accelerators and other processing elements. While cache coherency won't disappear anytime soon, it is increasingly being viewed as a luxury necessary to preserve a long-standing programming paradig... » read more

The Return Of DAC In-Person


Apart from masked faces everywhere, you could be excused for not knowing that there was a pandemic going on. Sure, the numbers were down, the show floor was smaller, and most of the parties didn't happen, but everyone was so happy to be able to bump elbows with their colleagues. Buttons were available for attendees to show the level of comfort they had with various types of greetings, from "... » read more

Amdahl Limits On AI


Software and hardware both place limits on how fast an application can run, but finding and eliminating the limitations is becoming more important in this age of multicore heterogeneous processing. The problem is certainly not new. Gene Amdahl (1922-2015) recognized the issue and published a paper about it in 1967. It provided the theoretical speedup for a defined task that could be expected... » read more

Gaps In The AI Debug Process


When an AI algorithm is deployed in the field and gives an unexpected result, it's often not clear whether that result is correct. So what happened? Was it wrong? And if so, what caused the error? These are often not simple questions to answer. Moreover, as with all verification problems, the only way to get to the root cause is to break the problem down into manageable pieces. The semico... » read more

AI/ML Workloads Need Extra Security


The need for security is pervading all electronic systems. But given the growth in data-center machine-learning computing, which deals with extremely valuable data, some companies are paying particular attention to handling that data securely. All of the usual data-center security solutions must be brought to bear, but extra effort is needed to ensure that models and data sets are protected ... » read more

HBM2E Raises The Bar For Memory Bandwidth


AI/ML training capabilities are growing at a rate of 10X per year driving rapid improvements in every aspect of computing hardware and software. HBM2E memory is the ideal solution for the high bandwidth requirements of AI/ML training, but entails additional design considerations given its 2.5D architecture. Designers can realize the full benefits of HBM2E memory with the silicon-proven memory s... » read more

Bandwidth Utilization Side-Channel On ML Inference Accelerators


Abstract—Accelerators used for machine learning (ML) inference provide great performance benefits over CPUs. Securing confidential model in inference against off-chip side-channel attacks is critical in harnessing the performance advantage in practice. Data and memory address encryption has been recently proposed to defend against off-chip attacks. In this paper, we demonstrate that bandwidth... » read more

Solving Real World AI Productization Challenges With Adaptive Computing


The field of artificial intelligence (AI) moves swiftly, with the pace of innovation only accelerating. While the software industry has been successful in deploying AI in production, the hardware industry – including automotive, industrial, and smart retail – is still in its infancy in terms of AI productization. Major gaps still exist that hinder AI algorithm proof-of-concepts (PoC) from b... » read more

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