Add release notes 1.2.0 and updated road map
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+---
+layout: page
+title: SystemML 1.2.0 Release Notes
+description: Project Release Notes
+group: nav-right
+---
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements. See the NOTICE file distributed with
+this work for additional information regarding copyright ownership.
+The ASF licenses this file to you under the Apache License, Version 2.0
+(the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+{% endcomment %}
+-->
+
+<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 }} 1.2.0 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 1.2.0 release was approved on Aug. 24th, 2018. The release includes enhancements, features, and additions as listed below.
+
+
+### New Builtin Functions/Operations/Scripts/Features
+- Factorization Machines
+- Support for functions with default parameters
+- `exists()` for checking of existing variables
+- Triangular matrix functions: `lower.tri()` and `upper.tri()`
+- New nary min/max operations
+- `as.matrix()` over list of scalars
+- Function calls with named function arguments
+- Convolution operations (forward/backward)
+- Maxpooling operations (forward)
+- Support for bias_add and bias_mult
+- Global constants
+- Added support for rowProd/colProd
+- DML eval function
+- New data type list for lists and structs
+
+### API
+- JMLC API extension for passing multiple dml scripts
+
+### Compiler & Runtime
+- Code motion framework
+- Global subexpression elimination
+- Optional rewrite for hoisting loop-invariant operations
+- Improved IPA constant propagation and replacement
+- ParFor Data Partitioning Rewrite on Hops instead of Statements
+- New rewrites for chains of comparisons
+- Extended rewrite framework for codegen plans
+- Improved parfor optimizer rewrite for in-place-update
+- Rework function block recompilation
+- Support rowMeans in codegen row templates
+
+### Performance Improvements
+- Improved multi-threading of unary aggregates
+- Reuse of fair scheduler pools in local parfor workers
+- Performance issues Spark ctable(X,Y) w/ large num distinct
+- Performance instruction generation
+- Performance sample operations
+- Performance ultra-sparse block operations
+- New native tsmm operator and its integration
+- Multi-threaded unary operations (e.g., exp, log, sigmoid)
+
+### Bug Fixes
+- Memory leak buffer pool due to missing variable cleanup
+- Missing buffer pool serialization of compressed matrices
+- Compilation failure on inferring size of reshapes w/ zero rows/columns
+- Incorrect result for min/max over matrices with NaNs
+- Missing support for external functions with variable number of outputs
+- Reblock ultra-sparse matrix fails with index out of bounds
+- Performance issue CSE on DAGs w/ many root nodes (e.g., resnet200)
+- Non-fused bias_add builtin creates incorrect results over sparse inputs
+- Inconsistent namespace naming depending on OS
+- Codegen failing on three-way multi-aggregate
+- Codegen optimizer failing for MLogreg special cases
+- Failing matrix market to binary reblock with zero rows/columns
+
+### Deprecated/Removed/Cleanup
+- Opt level 4
+- File-based removeEmpty()
+- Cleanup exception handling apis/compiler/runtime
+
+### Experimental
+- Parameter server: local backend and distributed
+- Sparsity estimators
+
+### [JIRA release notes](https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12342959&projectId=12319522)
diff --git a/_src/roadmap.html b/_src/roadmap.html
index 9dc3044..f247051 100644
--- a/_src/roadmap.html
+++ b/_src/roadmap.html
@@ -36,15 +36,17 @@
<section class="full-stripe full-stripe--alternate">
<div class="ml-container ml-container--narrow content-group">
<div class="col col-12">
- <h2>Planned for Future SystemML 1.2</h2>
+ <h2>Planned for Future Releases</h2>
<ul>
+ <li>Completion of Prior Experimental Features</li>
<li>Algorithms & builtin functions
<ul>
<li>NN layers-based factorization machines with regression & classification capabilities</li>
<li>NN optimization test suite with well known optimization test functions</li>
<li>Model selection & hyper parameter tuning</li>
<li>Additional distribution functions, e.g. weibull, gamma</li>
- <li>Generalization of operations, such as xor, and other operations</li>
+ <li>Time Series Analysis and Anomaly Detection</li>
+ <li>Scalable Decomposition Algorithms</li>
</ul>
</li>
<li>Enhanced Deep Learning support
@@ -73,6 +75,7 @@
<li>Ultra-sparse datasets</li>
</ul>
</li>
+ <li>Model Serving</li>
<li>Misc Runtime
<ul>
<li>NUMA-awareness (thread pools, matrix partitioning)</li>
@@ -83,38 +86,14 @@
</li>
<li>Misc Compiler
<ul>
- <li>Consolidate replicated compilation chain (e.g., diff APIs)</li>
<li>Holistic sum-product optimization and operator fusion</li>
- <li>Extended sparsity estimators</li>
- <li>Rewrites and compiler improvements for mini-batching including prefetching</li>
- <li>Parfor optimizer support for shared reads</li>
<li>SPOOF compiler improvement</li>
+ <li>Tree-based Data Structures</li>
+ <li>Global Dataflow Optimizations</li>
</ul>
</li>
- <li>APIs
- <ul>
- <li>Python Binding for JMLC API</li>
- </ul>
-
- </li>
-
-
- </ul>
- </div>
-
- <div class="col col-12">
- <h2>Feature Candidates for Future Releases</h2>
- <ul>
- <li>Completion of Prior Experimental Features</li>
- <li>Python DSL</li>
- <li>New Algorithms -- e.g. Decomposition Algorithms</li>
- <li>Common DSL Architecture</li>
- <li>R Interfaces: R DSL and R Wrappers</li>
- <li>Native Zeppelin Notebook Support</li>
- <li>Sum Product Optimizations</li>
- <li>Tree-based Data Structures</li>
- <li>Global Dataflow Optimizations</li>
<li>Tooling</li>
+ <li>Common DSL Architecture</li>
</ul>
</div>
@@ -122,6 +101,37 @@
<h2>Current Release</h2>
<ul>
<li>
+ <strong>SystemML 1.2.0 (<a href="release-notes/systemml-release-notes-1.2.0.html">released</a> in Aug, 2018)
+ <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12342959&projectId=12319522">details</a></strong>
+ <ul>
+ <li>New data type list for lists and structs</li>
+ <li>Built in deep learning functions, e.g. convolution, maxpooling, bias</li>
+ <li>DML eval function</li>
+ <li>Multiple new builtin functions, e.g. exists, lower.tri, upper.tri</li>
+ <li>Code motion, global subexpression elimination, rewrites for codegen</li>
+ <li>Performance improvements for ultra-sparse data and instruction generation
+ </ul>
+ </li>
+ <li>
+ Experimental Features
+ <ul>
+ <li>Parameter server</li>
+ <li>Sparsity estimators</li>
+ </ul>
+ </li>
+ <li>
+ Removals
+ <ul>
+ <li>Opt level 4</li>
+ </ul>
+ </li>
+ </ul>
+ </div>
+
+ <div class="col col-12">
+ <h2>Prior Releases</h2>
+ <ul>
+ <li>
<strong>SystemML 1.1.0 (<a href="release-notes/systemml-release-notes-1.1.0.html">released</a> in March, 2018)
<a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12319522&version=12342282">details</a></strong>
<ul>
@@ -133,12 +143,6 @@
<li>Performance improvements</li>
</ul>
</li>
- </ul>
- </div>
-
- <div class="col col-12">
- <h2>Prior Releases</h2>
- <ul>
<li>
<strong>SystemML 1.0.0 (<a href="release-notes/systemml-release-notes-1.0.0.html">released</a> in December, 2017)
<a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12319522&version=12338328">details</a></strong>
