AI Testing: Pushing Beyond DFT Architectures


Every day, more applications are deploying artificial intelligence (AI) system to increase automation beyond traditional systems. The continuous growth in computing demands of AI systems require designers to develop massive, highly parallel AI processor chips. Their large sizes and types of applications have a significant impact on their design and test methodologies. With thousands of repeated... » read more

Heterogeneous Computing Model Delivers Order-Of-Magnitude Performance Breakthrough


By Srinivas Kodiyalam (NVIDIA) and Samad Parekh (Synopsys) With the ever-increasing demand for more computing performance, the HPC industry is moving towards a heterogeneous computing model, where GPUs and CPUs work together to perform general-purpose computing tasks. In this heterogeneous computing model, the GPU serves as an accelerator to the CPU, to offload the CPU and to increase comput... » read more

Requirements For Exhaustive SoC Reset Domain Crossing Checks


It is common to read that the numbers of clock domains and power domains in system-on-chip (SoC) designs are increasing, but for some reason there is less discussion about resets. There is no doubt that the number of reset domains is also rising; studies have shown that the single reset of twenty years ago has been replaced by a complex network of 40-50 domains in many chips and even 150 in som... » read more

Find Bugs Early: On-The-Fly Code Correction For Design And Verification Productivity


The key rule for chip design and verification is that bugs must be found and fixed as early in the development process as possible. It is often said that catching a bug at each successive project stage multiplies the cost by ten. Bugs that escape verification and make their way to silicon are very expensive and time-consuming to fix. The ideal is to catch as many types of issues as possible as ... » read more

Timing Challenges In The Age Of AI Hardware


In recent years, we have seen a clear market trend towards dedicated integrated circuits (ASICs) that are much more efficient in performance and energy consumption than traditional general-purpose computers for processing AI workloads. These AI accelerators harden deep learning algorithm kernels into circuits, enable higher data ingestion bandwidth with local memory, and perform massively paral... » read more

AI And ML Applications Require Advanced Datapath Verification


In popular usage, the term “artificial intelligence” (AI) once conjured up images of robot armies subjugating humans or evil computers outsmarting their users, as in '2001: A Space Odyssey.' In recent years, AI has become a part of daily life for much of the planet’s population. People use voice commands to interact with their smartphones, smart speakers and even TV remote controls. Sophi... » read more

5 Predictions For AI Innovation In 2021


By Arun Venkatachar and Stelios Diamantidis Artificial intelligence (AI) has emerged as one of the most important watchwords in all of technology. The once-utopian vision of developing machines that can think and behave like humans is becoming more of a reality as engineering innovations enable the performance required to process and interpret previously unimaginable amounts of data efficien... » read more

Detecting Electrical Hazards Incurred By Inter-Voltage Domain Crossing In Custom SRAMs


Fast-growing markets, such as 5G, biotechnology, AI, and automotive, are driving a new wave of low-power semiconductor design requirements and, hence, more aggressive low-power management techniques are needed. Consequently, even large macros within a chip, such as SRAMs, now feature multiple voltage domains to limit power draw during light-sleep, deep-sleep, and shutdown-low-power modes. These... » read more

Virtual Prototyping For Power Electronics Systems


By Alan Courtay and Gobi Kengara Palayam Appavoo Every day, power electronics systems play a bigger role in our lives. All-electric and hybrid vehicles are now common on our streets. Electrification of the aerospace industry is accelerating, and observers expect hybrid and electric aircraft to make an impact over the next decade or two. Many industrial systems rely increasingly on electronic... » read more

A Machine Learning-Based Approach To Formality Equivalence Checking


By Avinash Palepu, Namrata Shekhar and Paula Neeley After a long and hard week, it is Friday night and you are ready to relax and unwind with a glass of wine, a sumptuous dinner and a great movie. You turn on Netflix and you expect that it will not only have plenty of pertinent suggestions for you, but also the most appropriate one based on all the previous movies and shows that you have wat... » read more

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