Computation-in-Memory

One of the most critical challenges for today’s and future data-intensive and big data problems (ranging from economics and business activities to public administration, from national security to many scientific research areas) is  data storage and analysis. The primary goal is to increase the understanding of processes by extracting highly useful values hidden in the huge volumes of data. The increase of the data size has already surpassed the capabilities of today’s computation architectures which suffer from the limited bandwidth (due to communication and memory-access bottlenecks), energy inefficiency and limited scalability (due to CMOS technology). 

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