The demand for artificial intelligence has grown significantly over the past decade, and this
growth has been fueled by advances in machine learning techniques and the ability to …

Moore's Law is a techno-economic model that has enabled the information technology
industry to double the performance and functionality of digital electronics roughly every 2 …

Transformers are slow and memory-hungry on long sequences, since the time and memory
complexity of self-attention are quadratic in sequence length. Approximate attention …

Smarter applications are making better use of the insights gleaned from data, having an
impact on every industry and research discipline. At the core of this revolution lies the tools …

Classical information retrieval systems such as BM25 rely on exact lexical match and carry
out search efficiently with inverted list index. Recent neural IR models shifts towards soft …

The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in
generating pathways and rate constants for rare events such as protein folding and protein …

Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …

In the present work, we describe a more accurate and efficient variant of the chain-of-
spheres algorithm (COSX) for exchange matrix computations. Higher accuracy for the …

Generalized tensor algebra is a prime candidate for acceleration via customized ASICs.
Modern tensors feature a wide range of data sparsity, with the density of non-zero elements …

Many practical applications lead to optimization problems that can either be stated as
quadratic programming (QP) problems or require the solution of QP problems on a lower …