Update docs

Author: github-actions[bot]

_sources/deeplearning_operators/gemv.md.txt

@@ -252,7 +252,7 @@ def splitk_gemv_vectorized(
     return main
 ```
 
-With vectorized read, now the kernel finishs in **~0.0084 ms**, which is getting close to cuBLAS performance.
+With vectorized read, now the kernel finishes in **~0.0084 ms**, which is getting close to cuBLAS performance.
 
 
 ## `tvm_thread_allreduce` Instead of `atomicAdd`

deeplearning_operators/gemv.html

@@ -699,7 +699,7 @@ <h2>Vectorized Reads<a class="headerlink" href="#vectorized-reads" title="Link t
     <span class="k">return</span> <span class="n">main</span>
 </pre></div>
 </div>
-<p>With vectorized read, now the kernel finishs in <strong>~0.0084 ms</strong>, which is getting close to cuBLAS performance.</p>
+<p>With vectorized read, now the kernel finishes in <strong>~0.0084 ms</strong>, which is getting close to cuBLAS performance.</p>
 </section>
 <section id="tvm-thread-allreduce-instead-of-atomicadd">
 <h2><code class="docutils literal notranslate"><span class="pre">tvm_thread_allreduce</span></code> Instead of <code class="docutils literal notranslate"><span class="pre">atomicAdd</span></code><a class="headerlink" href="#tvm-thread-allreduce-instead-of-atomicadd" title="Link to this heading">¶</a></h2>