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+---
+layout: page
+title: SystemML 1.1.0 Release Notes
+description: Project Release Notes
+group: nav-right
+---
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
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+
+<section class="full-stripe full-stripe--subpage-header clear-header">
+ <div class="ml-container ml-container--horizontally-center">
+ <div class="col col-12 content-group content-group--center-content content-group--center-align">
+ <h1>{{ site.data.project.name }} 1.1.0 Release Notes</h1>
+ </div>
+ </div>
+</section>
+
+<section class="full-stripe full-stripe--alternate">
+ <div class="ml-container">
+ <div class="col col-12 content-group content-group--medium-bottom-margin" markdown="1">
+
+The Apache SystemML 1.1.0 release was approved on March 28, 2018. The release includes enhancements, features, and additions as listed below.
+
+### New Builtin Functions/Operations
+- `ifelse`
+- `assert`
+- Deep learning builtin functions: `avg_pool`, `avg_pool_backward`
+- Second-order `eval`
+- Accumulator operator +=
+- Bitwise operators not, and, or, xor, & LShift, Rshift
+- Logical operator support over matrices AND/OR/NOT/XOR
+
+### Additional Layers in the NN library
+- Average pooling
+- Upsampling
+- Low-rank fully connected
+
+### New Capabilities/Features
+- Dense matrix blocks >16GB, and operations
+- Enable additional ParFor result aggregation operations
+- UDFs callable in expressions
+- Zero rows/columns matrices and updated operations such as removeEmpty
+- Matrix-matrix multiplication over compressed matrices
+- Extended Caffe2DML and Keras2DML APIs
+
+### Compiler & Runtime
+- Use common thread pool
+- Single-precision support for native conv2d and mm operations
+- Improved nnz maintenance, runtime propogation and memory management
+- Robustness for matrices with larger than int dimensions
+- [Experimental] Codegen extensions: operation support, extended optimizer, see SYSTEMML-2065
+
+### Performance Improvements
+- 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.
+
+### Bug Fixes
+- in APIs, performance, optimizer, runtime, GPU backend, Spark backend
+
+### Deprecate
+- Support for Spark 2.1 / 2.2 (make switch to newer ANTLR version)
+
+### [JIRA release notes](https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12319522&version=12342282)
