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<h1>Apache SystemDS<sup id="trademark">&trade;</sup> 1.2.0 Release Notes</h1>
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<p>The Apache SystemML 1.2.0 release was approved on Aug. 24th, 2018. The release includes enhancements, features, and additions as listed below.</p>
<h3 id="new-builtin-functionsoperationsscriptsfeatures">New Builtin Functions/Operations/Scripts/Features</h3>
<ul>
<li>Factorization Machines</li>
<li>Support for functions with default parameters</li>
<li><code class="language-plaintext highlighter-rouge">exists()</code> for checking of existing variables</li>
<li>Triangular matrix functions: <code class="language-plaintext highlighter-rouge">lower.tri()</code> and <code class="language-plaintext highlighter-rouge">upper.tri()</code></li>
<li>New nary min/max operations</li>
<li><code class="language-plaintext highlighter-rouge">as.matrix()</code> over list of scalars</li>
<li>Function calls with named function arguments</li>
<li>Convolution operations (forward/backward)</li>
<li>Maxpooling operations (forward)</li>
<li>Support for bias_add and bias_mult</li>
<li>Global constants</li>
<li>Added support for rowProd/colProd</li>
<li>DML eval function</li>
<li>New data type list for lists and structs</li>
</ul>
<h3 id="api">API</h3>
<ul>
<li>JMLC API extension for passing multiple dml scripts</li>
</ul>
<h3 id="compiler--runtime">Compiler &amp; Runtime</h3>
<ul>
<li>Code motion framework</li>
<li>Global subexpression elimination</li>
<li>Optional rewrite for hoisting loop-invariant operations</li>
<li>Improved IPA constant propagation and replacement</li>
<li>ParFor Data Partitioning Rewrite on Hops instead of Statements</li>
<li>New rewrites for chains of comparisons</li>
<li>Extended rewrite framework for codegen plans</li>
<li>Improved parfor optimizer rewrite for in-place-update</li>
<li>Rework function block recompilation</li>
<li>Support rowMeans in codegen row templates</li>
</ul>
<h3 id="performance-improvements">Performance Improvements</h3>
<ul>
<li>Improved multi-threading of unary aggregates</li>
<li>Reuse of fair scheduler pools in local parfor workers</li>
<li>Performance issues Spark ctable(X,Y) w/ large num distinct</li>
<li>Performance instruction generation</li>
<li>Performance sample operations</li>
<li>Performance ultra-sparse block operations</li>
<li>New native tsmm operator and its integration</li>
<li>Multi-threaded unary operations (e.g., exp, log, sigmoid)</li>
</ul>
<h3 id="bug-fixes">Bug Fixes</h3>
<ul>
<li>Memory leak buffer pool due to missing variable cleanup</li>
<li>Missing buffer pool serialization of compressed matrices</li>
<li>Compilation failure on inferring size of reshapes w/ zero rows/columns</li>
<li>Incorrect result for min/max over matrices with NaNs</li>
<li>Missing support for external functions with variable number of outputs</li>
<li>Reblock ultra-sparse matrix fails with index out of bounds</li>
<li>Performance issue CSE on DAGs w/ many root nodes (e.g., resnet200)</li>
<li>Non-fused bias_add builtin creates incorrect results over sparse inputs</li>
<li>Inconsistent namespace naming depending on OS</li>
<li>Codegen failing on three-way multi-aggregate</li>
<li>Codegen optimizer failing for MLogreg special cases</li>
<li>Failing matrix market to binary reblock with zero rows/columns</li>
</ul>
<h3 id="deprecatedremovedcleanup">Deprecated/Removed/Cleanup</h3>
<ul>
<li>Opt level 4</li>
<li>File-based removeEmpty()</li>
<li>Cleanup exception handling apis/compiler/runtime</li>
</ul>
<h3 id="experimental">Experimental</h3>
<ul>
<li>Parameter server: local backend and distributed</li>
<li>Sparsity estimators</li>
</ul>
<h3 id="jira-release-notes"><a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12342959&amp;projectId=12319522">JIRA release notes</a></h3>
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