The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …

This paper updates the survey of AI accelerators and processors from past three years. This
paper collects and summarizes the current commercial accelerators that have been publicly …

Existing tensor compilers have proven their effectiveness in deploying deep neural networks
on general-purpose hardware like CPU and GPU, but optimizing for neural processing units …

Advanced integration and packaging will drive the scaling of computing systems in the next
decade. Diversity in performance, cost and scale of the emerging systems implies that …

Smart computing on edge-devices has demonstrated huge potential for various application
sectors such as personalized healthcare and smart robotics. These devices aim at bringing …

Deep Learning (DL) acceleration support in CPUs has recently gained a lot of traction, with
several companies (Arm, Intel, IBM) announcing products with specialized matrix engines …

Upcoming LIGO–Virgo–KAGRA (LVK) observational runs offer new opportunities to probe
the central engines of extreme transient events. Cosmological gamma-ray bursts (GRBs) …

Stencil computations lie at the heart of many scientific and industrial applications. Stencil
algorithms pose several challenges on machines with cache based memory hierarchy, due …

Spatial computing devices have been shown to significantly accelerate stencil computations,
but have so far relied on unrolling the iterative dimension of a single stencil operation to …

Extremely high data rates at modern synchrotron and X-ray free-electron laser light source
beamlines motivate the use of machine learning methods for data reduction, feature …