Generative AI applications don’t need bigger memory, but smarter forgetting. When building LLM apps, start by shaping working memory. You delete a dependency. ChatGPT acknowledges it. Five responses ...

Memory is an integral component in every computer system, from the smartphones in our pockets to the giant data centers powering the world’s leading-edge AI applications. As AI continues to rise in ...

The adoption of in-memory computing platforms has steadily increased over the past decade, growing in popularity as tra­ditional disk-based databases could no lon­ger provide the performance and ...

Non-volatile memory is an important component in a wide range of high-performance embedded applications. Especially, many consumer, industrial, and medical applications need increased re-writability ...

Over the past decade, much of the focus with machine learning has been on CPUs and accelerators, primarily GPUs but also custom ASICs, with advances in the chip architecture aimed at boosting parallel ...

A process may map files to its address space, thereby creating a 1-to-1 equivalence between the files’ data and its corresponding memory-mapped region. Memory mapping has several uses: Dynamic loading ...

A new technical paper titled “Leveraging Chiplet-Locality for Efficient Memory Mapping in Multi-Chip Module GPUs” was published by researchers at Electronics and Telecommunications Research Institute ...

Context windows of AI models, which indicate the ability of a model to “remember” information, have increased over time. However, researchers have suggested new ways to increase long-term memory of AI ...

The type of memory a designer selects for an embedded project drives overall system operation and performance, so obviously this is a very important decision. Whether the system runs on batteries or ...

Selecting the right amount of flash memory for an embedded application can be challenging. You want to make sure that you have enough memory to protect for future features, firmware updates, and more.