Protecting Chiplet Architectures With Hardware Security


Chiplets are gaining significant traction as they provide compelling benefits for advancing semiconductor performance, costs, and time to market. With Moore’s Law slowing, building more powerful chips translates into building bigger chips. But with chip dimensions pushing up against reticle limits, growing the size of chips is increasingly impractical. Chiplets offer a new path forward by dis... » read more

Chips Listening To Gibberish


We all talk gibberish once in a while. At least, I do. I might be in a silly mood, thinking aloud, listening to music or talking over the phone using my headphones (they are quite small, and if you don’t notice them, you could think I am crazy). Regardless of the circumstances, I mean no harm, I promise. However, it’s still possible that a passer-by could get distracted trying to figure out... » read more

Secure Silicon Lifecycle Management Architecture For Functional Safety


The rapid growth of electronics for automotive applications fueled by advanced ADAS systems pose new challenges for complex SoC design and Silicon Lifecycle Management (SLM) in the supply chain as well as in-field monitoring and management of the population of chips. In these modern complex devices, ensuring the correct and safe operation requires not only functional safety to check for reli... » read more

AI Design In Korea


Like many in the semiconductor design businesses, Arteris IP is actively working with the Korean chip companies. This shouldn’t be a surprise. If a company is building an SoC of any reasonable size, it needs network-on-chip (NoC) interconnect for optimal QoS (bandwidth and latency regulation and system-level arbitration) and low routing congestion, even in application-centric designs such as ... » read more

One More Time: TOPS Do Not Predict Inference Throughput


Many times you’ll hear vendors talking about how many TOPS their chip has and imply that more TOPS means better inference performance. If you use TOPS to pick your AI inference chip, you will likely not be happy with what you get. Recently, Vivienne Sze, a professor at MIT, gave an excellent talk entitled “How to Evaluate Efficient Deep Neural Network Approaches.” Slides are also av... » read more

How Cybersecurity Is Driving Business Forward


Cybersecurity is a topic that continues to grow in importance for both the general population and those who work in the tech industry. While news headlines about security breaches affecting various companies are now almost a daily occurrence, many still don’t understand the responsibility that every one of us has to keep our own personal and workplace networks secure. This October, Synopsys w... » read more

One SerDes Solution Doesn’t Fit All


Way back in the 1960s, E. Rent, who was working at IBM at the time, noticed a connection between the number of pins P on integrated circuits being used and the number of gates G on the integrated circuits. It was a power law, where the number of pins was cGR where c and R are constants. Actually, traditionally a Greek rho is used instead of R. It usually has a value between 0.5 and 0.8. If R... » read more

Choosing The Right Hardware Root Of Trust


A Root of Trust is broadly defined as the security foundation for a semiconductor or electronic system. Any secure function performed by the device or system relies in whole or in part on that Root of Trust. The Root of Trust typically handles chip and device identities, cryptographic functions, stores and manages cryptographic keys, and handles one or more secure processes that provides the fo... » read more

Making Everything Linux-Capable


It's not clear how the edge will play out or what will be the winning formula from a hardware standpoint. But for everything beyond the end device, and possibly even including the end device, a key prerequisite will be the ability to run Linux. That means at least one processor or core within the hardware will need to run 64-bit software. In addition, systems will need to have enough storage... » read more

For AI Hardware, Power Optimization Starts With Software And Ends At Silicon


Artificial intelligence (AI) processing hardware has emerged as a critical piece of today’s tech innovation. AI hardware architecture is very symmetric with large arrays of up to thousands of processing elements (tiles), leading to billion+ gate designs and huge power consumption. For example, the Tesla auto-pilot software stack consumes 72W of power, while the neural network accelerator cons... » read more

← Older posts