tag: Synopsys

Monitoring Chips On Many Levels
By Bryon Moyer - 06 Apr, 2021 - Comments: 1

Monitoring is an important trend for optimizing yield, performance, and uptime in systems that use complex integrated circuits, but not all monitoring is the same. In fact, there are multiple levels of monitors. In many cases, they can be used together to help solve problems when something is amiss. They also can be used to help identify who in the supply chain owns the fix. “If the sys... » read more

Security For Cars That Are Smartphones On Wheels
By Taylor Amerding - 06 Apr, 2021 - Comments: 1

Your modern car is a computer on wheels—potentially hundreds of computers on a set of wheels. Heck, even the wheels are infested with computers—what do you think prompts that little light on your dashboard to come on if your tire pressure is low? And computers don’t just run your infotainment system, backup camera, dashboard warning lights, and the voice that tells you to buckle your seat... » read more

Finding And Fixing Design And Testbench Coding Errors On The Fly
By Synopsys - 06 Apr, 2021 - Comments: 0

Two things are certain in chip verification: as many bugs as possible must be found and fixed before fabrication, and this must happen as early as possible in the development process. The much-desired “shift left” in verification requires that advanced analysis and debug technologies be available to engineers from the earliest stages of the project. It is preferable that many classes of err... » read more

Week In Review: Auto, Security, Pervasive Computing
By SE Staff - 02 Apr, 2021 - Comments: 0

Pervasive computing — IoT, edge, cloud, data center, and back Arm announced its Armv9 architecture, which is designed for secure, pervasive computing that can run in more types of AI systems. Because most data will be touching an Arm-based chip in the near future — whether on the edge, IoT, or data center — Arm enhanced the security, in addition to improving performance and AI/ML capabil... » read more

Safeguarding Data Over PCIe & CXL In Data Centers
By Dana Neustadter - 01 Apr, 2021 - Comments: 0

As more devices enter the market and drive exponential growth of data in the cloud, cloud computing is going through a significant overhaul. The increasing presence of “hyperscale” cloud providers for big data and analytics, 5G for rapid IoT connectivity, and the wide use of AI for natural data processing and for extracting insights are compounding both the amount of connected data and the ... » read more

New Uses For AI
By Ed Sperling - 01 Apr, 2021 - Comments: 0

AI is being embedded into an increasing number of technologies that are commonly found inside most chips, and initial results show dramatic improvements in both power and performance. Unlike high-profile AI implementations, such as self-driving cars or natural language processing, much of this work flies well under the radar for most people. It generally takes the path of least disruption, b... » read more

Privacy Protection A Must For Driver Monitoring
By Ann Mutschler - 01 Apr, 2021 - Comments: 1

Driver monitoring systems are so tied into a vehicle's architecture that soon the driver will not be able to opt out because the vehicle will only operate if the driver is detected and monitored. This is raising privacy concerns about whether enough security is in place for the data to remain private. At the very least, laws and regulations in every geography where the vehicle will operate a... » read more

CISO’s Guide To Sensitive Data Protection
By Synopsys - 31 Mar, 2021 - Comments: 0

Emerging data protection and privacy laws are causing organizations to scramble to implement strategies that address regulatory compliance and data security governance. And the SolarWinds software supply chain attack, in which attackers inserted a malicious back door into its network software release that later led to sensitive data exposure, further underscores the need to secure the DevSecOps... » read more

Blog Review: March 31
By Jesse Allen - 31 Mar, 2021 - Comments: 0

Arm's Pavel Rudko considers several common approaches used to get better performance for neural network inference on mobile devices, such as optimizing and pruning the model and using different processing units to execute different workloads in parallel. Siemens EDA's Ray Salemi introduces basic concepts of using Python for verification and how to get Python to talk to an RTL device-under-te... » read more

Computing Where Data Resides
By Ann Mutschler - 29 Mar, 2021 - Comments: 3

Computational storage is starting to gain traction as system architects come to grips with the rising performance, energy and latency impacts of moving large amounts of data between processors and hierarchical memory and storage. According to IDC, the global datasphere will grow from 45 zettabytes in 2019 to 175 by 2025. But that data is essentially useless unless it is analyzed or some amou... » read more

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