The problem of compiler optimization of sparse codes is well known and no satisfactory solutions have been found yet. One of the major obstacles is formed by the fact that sparse programs explicitly ...

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Their resulting meta-learning sparse compression networks (MSCN) are able to effectively represent diverse data modalities such as images, manifolds, signed distance functions, 3D shapes and scenes; ...

We pinpoint the role of sparse matrix formats implemented in the neuro-simulator ANNarchy with respect to computation time. Rather than asking the user to identify the best data structures required ...

In this paper various methods of Data structure selection methodologies along with overview of delays data structure selection till compilation phase is discussed. Efficient code is generated for ...

The non-negative matrix factorization encounters both computational and theoretical challenge with such high-dimensional data, i.e., there is no guarantee for a sparse and part-based representation of ...

A sparse matrix is a matrix in which most of the elements are zero. This is a program in java that takes in two matrices A and B and finds the transpose and the product of them. This is a project ...

We present CheSS, the “Chebyshev Sparse Solvers” library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The ...