Yes, that simple question is, in the modern Nvidia world that has come to dominate AI training and to a certain extent HPC simulation and modeling, heretical. But given that CPUs are in many cases ...

Abstract: Using high-level synthesis techniques, this paper proposes an adaptable high-performance streaming dataflow engine for sparse matrix dense vector multiplication (SpMV) suitable for embedded ...

Abstract: Non-negative matrix factorization (NMF) is becoming increasingly popular in many research fields due to its particular properties of semantic interpretability and part-based representation.

Quantum computers can outperform their classical counterparts at some tasks, but the full scope of their power is unclear. A new quantum algorithm hints at the possibility of far-reaching applications ...

The integration of multi-omics data, including genomics, transcriptomics, proteomics, and metabolomics, has revolutionized our understanding of complex biological processes. This topic is centered ...

to the genome generation options, which is used by CellRanger to generate STAR genomes. It will generate sparse suffixs array which has an additional benefit of fitting into 16GB of RAM. However, it ...

For (dense and sparse) vector and matrix classes Shark relies on Boost uBLAS. Many higher level algorithms (such as singular value decomposition) are still implemented by the library itself.

The GTM and k-GTM algorithms are implemented in GTMapTool (URLs). We used the Jaccard similarity matrix of FDR-significant pathways as input for the algorithm, where each pathway is encoded by a ...