65 research outputs found
Automatic Generation of Efficient Sparse Tensor Format Conversion Routines
This paper shows how to generate code that efficiently converts sparse
tensors between disparate storage formats (data layouts) such as CSR, DIA, ELL,
and many others. We decompose sparse tensor conversion into three logical
phases: coordinate remapping, analysis, and assembly. We then develop a
language that precisely describes how different formats group together and
order a tensor's nonzeros in memory. This lets a compiler emit code that
performs complex remappings of nonzeros when converting between formats. We
also develop a query language that can extract statistics about sparse tensors,
and we show how to emit efficient analysis code that computes such queries.
Finally, we define an abstract interface that captures how data structures for
storing a tensor can be efficiently assembled given specific statistics about
the tensor. Disparate formats can implement this common interface, thus letting
a compiler emit optimized sparse tensor conversion code for arbitrary
combinations of many formats without hard-coding for any specific combination.
Our evaluation shows that the technique generates sparse tensor conversion
routines with performance between 1.00 and 2.01 that of hand-optimized
versions in SPARSKIT and Intel MKL, two popular sparse linear algebra
libraries. And by emitting code that avoids materializing temporaries, which
both libraries need for many combinations of source and target formats, our
technique outperforms those libraries by 1.78 to 4.01 for CSC/COO to
DIA/ELL conversion.Comment: Presented at PLDI 202
A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome
Citation: Chapman, J. A., Mascher, M., Buluç, A., Barry, K., Georganas, E., Session, A., . . . Rokhsar, D. S. (2015). A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome. Genome Biology, 16(1). doi:10.1186/s13059-015-0582-8Polyploid species have long been thought to be recalcitrant to whole-genome assembly. By combining high-throughput sequencing, recent developments in parallel computing, and genetic mapping, we derive, de novo, a sequence assembly representing 9.1 Gbp of the highly repetitive 16 Gbp genome of hexaploid wheat, Triticum aestivum, and assign 7.1 Gb of this assembly to chromosomal locations. The genome representation and accuracy of our assembly is comparable or even exceeds that of a chromosome-by-chromosome shotgun assembly. Our assembly and mapping strategy uses only short read sequencing technology and is applicable to any species where it is possible to construct a mapping population. © 2015 Chapman et al. licensee BioMed Central.Additional Authors: Muehlbauer, G. J.;Stein, N.;Rokhsar, D. S
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