As the limits of transistor technology are approached, feature size in integrated circuit
transistors has been reduced very near to the minimum physically-realizable channel length …

In recent years, the limits of the multicore approach emerged in the so-called “dark silicon”
issue and diminishing returns of an ever-increasing core count. Hardware manufacturers …

Processing-using-DRAM has been proposed for a limited set of basic operations (ie, logic
operations, addition). However, in order to enable full adoption of processing-using-DRAM …

Memorization is an essential functionality that enables today's machine learning algorithms
to provide a high quality of learning and reasoning for each prediction. Memorization gives …

Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …

In this paper, we propose BioHD, a novel genomic sequence searching platform based on
Hyper-Dimensional Computing (HDC) for hardware-friendly computation. BioHD transforms …

Transformer-based models are state-of-the-art for many machine learning (ML) tasks.
Executing Transformer usually requires a long execution time due to the large memory …

Today's applications generate a large amount of data that need to be processed by learning
algorithms. In practice, the majority of the data are not associated with any labels …

Recent work demonstrated the promise of using resistive random access memory (ReRAM)
as an emerging technology to perform inherently parallel analog domain in-situ matrix …

Memristor-aided logic (MAGIC) is a technique for performing in-memory computing using
memristive devices. The design of a MAGIC NOR gate has been described in detail, and it …