Caching intent largely hasn’t changed since we started using the concept – to reduce average latency in memory accesses and to reduce average power consumption in off-chip reads and writes. The architecture started out simple enough, a small memory close to a processor, holding most-recently accessed instructions and data … Read More
If you follow my blogs you know that Arteris IP is very active in these areas, leveraging their central value in network-on-chip (NoC) architectures. Kurt Shuler has put together a front-to-back white-paper to walk you through the essentials of AI, particularly machine learning (ML) and its application for example in cars.
He… Read More
No, I’m not going to talk about in-memory-compute architectures. There’s interesting work being done there but here I’m going to talk here about mainstream architectures for memory support in Machine Learning (ML) designs. These are still based on conventional memory components/IP such as cache, register files, SRAM and various… Read More
Machine learning (ML), and neural nets (NNs) as a subset of ML, are blossoming in all sorts of applications, not just in the cloud but now even more at the edge. We can now find them in our phones, in our cars, even in IoT applications. We have all seen applications for intelligent vision (e.g. pedestrian detection) and voice recognition… Read More
If a CPU or CPU cluster in an SoC is the brain of an SoC, then the interconnect is the rest of the central nervous system, connecting all the other processing and IO functions to that brain. This interconnect must enable these functions to communicate with the brain, with multiple types of memory, and with each other as quickly and predictably… Read More