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JianyiCheng/HLS-benchmarks: HLS_Benchmarks_First_Release

Jianyi Cheng


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    <dct:title>JianyiCheng/HLS-benchmarks: HLS_Benchmarks_First_Release</dct:title>
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    <dct:description>&lt;p&gt;First release of my HLS benchmarks. The benchmarks include:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;&lt;em&gt;gSum&lt;/em&gt; 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.&lt;/li&gt; &lt;li&gt;&lt;em&gt;gSumIf&lt;/em&gt; is similar to &lt;em&gt;gSum&lt;/em&gt; but the SS function returns one of two polynomial expressions based on the value of the difference.&lt;/li&gt; &lt;li&gt;&lt;em&gt;sparseMatrixPower&lt;/em&gt; performs dot product of two matrices, which skips the operation when the weight is zero.&lt;/li&gt; &lt;li&gt;&lt;em&gt;histogram&lt;/em&gt; sums various weight onto the corresponding features but also in a sparse form.&lt;/li&gt; &lt;li&gt;&lt;em&gt;getTanh&lt;/em&gt; performs the approximated function &lt;em&gt;tanh(x)&lt;/em&gt; onto an array of integers using the CORDIC algorithm and a polynomial function.&lt;/li&gt; &lt;li&gt;&lt;em&gt;getTanh(double)&lt;/em&gt; is similar to &lt;em&gt;getTanh&lt;/em&gt; but uses an array of doubles.&lt;/li&gt; &lt;li&gt;&lt;em&gt;BNNKernel&lt;/em&gt; is a small BNN kernel with LUT function as XOR.&lt;/li&gt; &lt;/ul&gt;</dct:description>
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