Vision-based navigation has become increasingly important in a variety of space
applications for enhancing autonomy and dependability. Future missions, such as active …

A number of resource-intensive applications, such as augmented reality, natural language
processing, object recognition, and multimedia-based software are pushing the …

With the ever increasing prevalence of neural networks and the upheaval from the language
models, it is time to rethink neural acceleration. Up to this point, the broader research …

Electronic structure theory (especially quantum chemistry) has thrived and has become
increasingly relevant to a broad spectrum of scientific endeavors as the sophistication of …

Deep learning has revolutionized computer vision and other fields since its big bang in
2012. However, it is challenging to deploy Deep Neural Networks (DNNs) into real-world …

Energy efficiency is the primary impediment in the path to exascale computing.
Consequently, the high-performance computing community is increasingly interested in low …

In this paper, a new method for accelerating the 2D direct Convolution operation on x86/x64
processors is presented. It includes efficient vectorization by using SIMD intrinsics, bit …

Recent applications in low-power (1-20 mW) near-sensor computing require the adoption of
floating-point arithmetic to reconcile high precision results with a wide dynamic range. In this …

Hyperdimensional computing (HDC) is a novel computing framework that has gained
significant attention for its ability to accelerate machine learning algorithms. Its fast learning …

Fog and mobile edge computing is a paradigm that augments resource‐scarce mobile
devices with resource‐rich network servers to enable ubiquitous computing. Smartphone …