6 research outputs found
Evidence of phonon-assisted tunnelling in electrical conduction through DNA molecules
We propose a phonon-assisted tunnelling model for explanation of conductivity
dependence on temperature and temperature-dependent I-V characteristics in
deoxyribonucleic acid (DNA) molecules. The capability of this model for
explanation of conductivity peculiarities in DNA is illustrated by comparison
of the temperature dependent I-V data extracted from some articles with
tunnelling rate dependences on temperature and field strength computed
according to the phonon-assisted tunnelling theory.
PACS Codes: 87.15.-v, 71.38.-k, 73.40.GkComment: 6 pages, 3 figure
Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs
Connected components and spanning forest are fundamental graph algorithms due
to their use in many important applications, such as graph clustering and image
segmentation. GPUs are an ideal platform for graph algorithms due to their high
peak performance and memory bandwidth. While there exist several GPU
connectivity algorithms in the literature, many design choices have not yet
been explored. In this paper, we explore various design choices in GPU
connectivity algorithms, including sampling, linking, and tree compression, for
both the static as well as the incremental setting. Our various design choices
lead to over 300 new GPU implementations of connectivity, many of which
outperform state-of-the-art. We present an experimental evaluation, and show
that we achieve an average speedup of 2.47x speedup over existing static
algorithms. In the incremental setting, we achieve a throughput of up to 48.23
billion edges per second. Compared to state-of-the-art CPU implementations on a
72-core machine, we achieve a speedup of 8.26--14.51x for static connectivity
and 1.85--13.36x for incremental connectivity using a Tesla V100 GPU