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<h1>Apache SystemDS<sup id="trademark">&trade;</sup> 1.1.0 Release Notes</h1>
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<p>The Apache SystemML 1.1.0 release was approved on March 28, 2018. The release includes enhancements, features, and additions as listed below.</p>
<h3 id="new-builtin-functionsoperations">New Builtin Functions/Operations</h3>
<ul>
<li><code class="language-plaintext highlighter-rouge">ifelse</code></li>
<li><code class="language-plaintext highlighter-rouge">assert</code></li>
<li>Deep learning builtin functions: <code class="language-plaintext highlighter-rouge">avg_pool</code>, <code class="language-plaintext highlighter-rouge">avg_pool_backward</code></li>
<li>Second-order <code class="language-plaintext highlighter-rouge">eval</code></li>
<li>Accumulator operator +=</li>
<li>Bitwise operators not, and, or, xor, &amp; LShift, Rshift</li>
<li>Logical operator support over matrices AND/OR/NOT/XOR</li>
</ul>
<h3 id="additional-layers-in-the-nn-library">Additional Layers in the NN library</h3>
<ul>
<li>Average pooling</li>
<li>Upsampling</li>
<li>Low-rank fully connected</li>
</ul>
<h3 id="new-capabilitiesfeatures">New Capabilities/Features</h3>
<ul>
<li>Dense matrix blocks &gt;16GB, and operations</li>
<li>Enable additional ParFor result aggregation operations</li>
<li>UDFs callable in expressions</li>
<li>Zero rows/columns matrices and updated operations such as removeEmpty</li>
<li>Matrix-matrix multiplication over compressed matrices</li>
<li>Extended Caffe2DML and Keras2DML APIs</li>
</ul>
<h3 id="compiler--runtime">Compiler &amp; Runtime</h3>
<ul>
<li>Use common thread pool</li>
<li>Single-precision support for native conv2d and mm operations</li>
<li>Improved nnz maintenance, runtime propogation and memory management</li>
<li>Robustness for matrices with larger than int dimensions</li>
<li>[Experimental] Codegen extensions: operation support, extended optimizer, see SYSTEMML-2065</li>
</ul>
<h3 id="performance-improvements">Performance Improvements</h3>
<ul>
<li>sparse left indexing, sparse reshape, ultra-sparse transpose, ultra-sparse rand, binary in-place operations, sparse relu backward, maxpooling, sparse im2col, ultra-sparse conv2d, read of short-wide sparse matrices, avoid unnecessary evictions, lock-free statistics maintenance, spark cpmm, spark aggregates, spark reshape, spark binary ops, etc.</li>
</ul>
<h3 id="bug-fixes">Bug Fixes</h3>
<ul>
<li>in APIs, performance, optimizer, runtime, GPU backend, Spark backend</li>
</ul>
<h3 id="deprecate">Deprecate</h3>
<ul>
<li>Support for Spark 2.1 / 2.2 (make switch to newer ANTLR version)</li>
</ul>
<h3 id="jira-release-notes"><a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12319522&amp;version=12342282">JIRA release notes</a></h3>
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