The dynamic interplay between processor speed and memory access times has rendered cache performance a critical determinant of computing efficiency. As modern systems increasingly rely on hierarchical ...

Exponential increases in data and demand for improved performance to process that data has spawned a variety of new approaches to processor design and packaging, but it also is driving big changes on ...

As GPU’s become a bigger part of data center spend, the companies that provide the HBM memory needed to make them sing are benefitting tremendously. AI system performance is highly dependent on memory ...

Memory swizzling is the quiet tax that every hierarchical-memory accelerator pays. It is fundamental to how GPUs, TPUs, NPUs, ...

Hardware developers of deep learning neural networks (DNN) have a universal complaint – they need more and more memory capacity with high performance, low cost and low power. As artificial ...

We have been excited about the possibilities of adding tiers of memory to systems, particularly persistent memories that are less expensive than DRAM but offer similar-enough performance and ...

If you reduce systems down to their bare essentials, everything exists in those systems to manipulate data in memory, and like human beings, all that really exists for any of us is what is in memory.

When we reviewed Ryzen's latest iteration we briefly checked out how DDR4-3200 CL14 compared to the DDR4-3600 CL16 memory that AMD supplied to us, as they claimed that was an optimal configuration.