Jianyi Cheng
2019-12-03
<p>First release of my HLS benchmarks. The benchmarks include:</p>
<ul>
<li><em>gSum</em> sums a number of polynomial results from the array elements that meet the given conditions where the difference between two elements from the arrays is non-negative.</li>
<li><em>gSumIf</em> is similar to <em>gSum</em> but the SS function returns one of two polynomial expressions based on the value of the difference.</li>
<li><em>sparseMatrixPower</em> performs dot product of two matrices, which skips the operation when the weight is zero.</li>
<li><em>histogram</em> sums various weight onto the corresponding features but also in a sparse form.</li>
<li><em>getTanh</em> performs the approximated function <em>tanh(x)</em> onto an array of integers using the CORDIC algorithm and a polynomial function.</li>
<li><em>getTanh(double)</em> is similar to <em>getTanh</em> but uses an array of doubles.</li>
<li><em>BNNKernel</em> is a small BNN kernel with LUT function as XOR.</li>
</ul>
https://doi.org/10.5281/zenodo.3561115
oai:zenodo.org:3561115
Zenodo
https://github.com/JianyiCheng/HLS-benchmarks/tree/v1.0
https://doi.org/10.5281/zenodo.3561114
info:eu-repo/semantics/openAccess
GNU General Public License v2.0 or later
https://www.gnu.org/licenses/old-licenses/gpl-2.0-standalone.html
JianyiCheng/HLS-benchmarks: HLS_Benchmarks_First_Release
info:eu-repo/semantics/other