Computing Low-Rank Approximation of a Dense Matrix on Multicore CPUs with a GPU and Its Application to Solving a Hierarchically Semiseparable Linear System of Equations

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/sp/volume-2015/246019/figures/246019.fig.008a.svgz" name="246019.fig.008a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Breakdown of factorization time</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/sp/volume-2015/246019/figures/246019.fig.008b.svgz" name="246019.fig.008b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Comparison with QP3 on random matrices</td></tr></table>

<div>Performance of the QP3 GPU-implementation on random short-wide matrices.</div>

Scientific Programming

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Figure 8

Figure 8: Computing Low-Rank Approximation of a Dense Matrix on Multicore CPUs with a GPU and Its Application to Solving a Hierarchically Semiseparable Linear System of Equations 

Figure 8 | Computing Low-Rank Approximation of a Dense Matrix on Multicore CPUs with a GPU and Its Application to Solving a Hierarchically Semiseparable Linear System of Equations 