forward port HSF#231 (HSF#236)

* forward port PR 231

* address comments by Graeme

* Update proposal_TMVATensorFlow.md

* Update project_TMVA.md

_activities/gsoc.md

@@ -15,19 +15,18 @@ and analyze petabytes data from high-energy physics experiments, such as the Lar
 hosted at the CERN laboratory in Geneva, Switzerland. 
 Some of the questions that we collectively ask are: 
 
-- what are the fundamental blocks that make up our Universe? 
+- what are the fundamental blocks that make up our Universe?
 - what is the nature of dark matter and dark energy?
-- what is the nature of the asymmetry between matter and antimatter? 
-- what was early Universe like? 
+- what is the nature of the asymmetry between matter and antimatter?
+- what was early Universe like?
 
 To answer these questions, particle physicists build software to simulate and analyze what happens in particle physics detectors.
 
-The CERN software for experiments (CERN-SFT) group has participated in the GSoC since 2011. 
-Since 2017 the program has expanded to involve the high-energy physics community under the umbrella of the HEP Software Foundation.
+The CERN software for experiments (CERN-SFT) group has participated in the GSoC since 2011. Since 2017 the program has expanded to involve the high-energy physics community under the umbrella of the HEP Software Foundation.
 
-Information from last year's GSoC can be found [here](/gsoc/2017/index.html). For 2018 the 
-HSF is again applying for participation in the program. If you are 
-interested in the GSoC program contact us using the HSF GSoC mailing list: [[email protected]](mailto:[email protected]).
+Information from last year’s GSoC can be found [here](/gsoc/2017/index.html). In 2018 CERN-HSF is again applying for participation in the program. 
+
+If you are interested in the GSoC program contact us using the HSF GSoC mailing list: [[email protected]](mailto:[email protected]).
 
 Instructions for participating projects and mentors can be found [here](/gsoc/guideline.html).
 

_gsocorgs/2018/epfl.md

@@ -0,0 +1,11 @@
+---
+title: "École polytechnique fédérale de Lausanne"
+author: "Omar Zapata"
+layout: default
+organization: EPFL
+logo: Logo_EPFL.png
+description: |
+  The École polytechnique fédérale de Lausanne (EPFL) is a research institute and university in Lausanne, Switzerland, that specializes in natural sciences and engineering.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/eth.md

@@ -0,0 +1,11 @@
+---
+title: "Eidgenössische Technische Hochschule Zürich"
+author: "Omar Zapata"
+layout: default
+organization: ETH
+logo: Eth-zurich_logo.png
+description: |
+  ETH Zurich (Swiss Federal Institute of Technology in Zurich; German: Eidgenössische Technische Hochschule Zürich) is a science, technology, engineering and mathematics university in the city of Zürich, Switzerland.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/florida.md

@@ -0,0 +1,11 @@
+---
+title: "University of Florida"
+author: "Omar Zapata"
+layout: default
+organization: Florida
+logo: ufl_logo.jpg
+description: |
+  University of Florida is a public institution that was founded in 1853.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/fsu.md

@@ -0,0 +1,11 @@
+---
+title: "Florida State University"
+author: "Omar Zapata"
+layout: default
+organization: FSU
+logo: fsu_logo.jpg
+description: |
+  Florida State University is a public institution that was founded in 1851.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/kit.md

@@ -0,0 +1,11 @@
+---
+title: "Karlsruhe Institute of Technology"
+author: "Omar Zapata"
+layout: default
+organization: KIT
+logo: kit_logo.png
+description: |
+  The Karlsruhe Institute of Technology is a public research university and one of the largest research and education institutions in Germany.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/lut.md

@@ -0,0 +1,11 @@
+---
+title: "Lulea University of Technology"
+author: "Omar Zapata"
+layout: default
+organization: LUT
+logo: lut_logo.jpg
+description: |
+  Lulea University of Technology (Swedish: Luleå tekniska universitet) of Sweden is Scandinavia's northernmost university of technology.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/oproject.md

@@ -0,0 +1,13 @@
+---
+title: "O Project"
+author: "Omar Zapata"
+layout: default
+organization: OProject
+logo: oproject-logo.png
+description: |
+  [OProject](http://oproject.org) Open source organization, specialized in development  of advaced scientfic software with ROOT, focused  mathematical/statistical tools, machine learning and high performance computing.
+---
+
+![Oproject](/images/oproject-banner.png){:.center-image}
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/udea.md

@@ -0,0 +1,10 @@
+---
+title: "University of Antioquia"
+author: "Omar Zapata"
+layout: default
+organization: UdeA
+description: |
+   Established in 1803, Universidad de Antioquia is a government-run public university based in Medellín, Colombia.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/uoldenburg.md

@@ -0,0 +1,11 @@
+---
+title: "Universitaet Oldenburg"
+author: "Omar Zapata"
+layout: default
+organization: UOldenburg
+logo: Uni_oldenburg_logo.png
+description: |
+  The Carl von Ossietzky University of Oldenburg (German: Carl von Ossietzky Universität Oldenburg) is a university located in Oldenburg, Germany.
+---
+
+{% include gsoc_proposal.ext %}

_gsocorgs/2018/uta.md

@@ -0,0 +1,11 @@
+---
+title: "University of Texas at Arlington"
+author: "Omar Zapata"
+layout: default
+organization: UTA
+logo: UTArlington_logo.png
+description: |
+  The University of Texas at Arlington (UTA or UT Arlington) is a public research university located in Arlington, Texas, midway between Dallas and Fort Worth.
+---
+
+{% include gsoc_proposal.ext %}

_gsocprojects/2018/project_FALCON.md

@@ -0,0 +1,10 @@
+---
+
+project: FALCON
+layout: default
+logo: falcon_logo.png
+description: |
+  Falcon is an ultra-fast non-parametric detector simulation package that automatically abstracts detector response, usually done by hand in fast-simulators used by particle physics experiments.
+---
+
+{% include gsoc_project.ext %}

_gsocprojects/2018/project_TMVA.md

@@ -0,0 +1,10 @@
+---
+project: TMVA
+layout: default
+logo: tmva_logo.gif
+description: |
+  Toolkit for Multivariate Analysis (TMVA) is a multi-purpose machine learning toolkit integrated into the ROOT scientific software framework, used in many particle physics data analyses and applications.
+---
+
+
+{% include gsoc_project.ext %}

_gsocproposals/2017/proposal_ROOTmpi.md

@@ -34,6 +34,7 @@ By standardizing the way different machines communicate during a running process
 **Mentors**: 
 
   * Omar Zapata  [email protected]
+  * Diego Restrepo [email protected]
   * Lorenzo Moneta  [email protected]
 
 **Links**:

_gsocproposals/2018/proposal_FALCON.md

@@ -0,0 +1,31 @@
+---
+title: Optimization of the ultra-fast detector simulation package FALCON and multi-objective regression
+layout: gsoc_proposal
+project: FALCON
+year: 2018
+organization: 
+ - FSU
+ - Florida
+ - UdeA
+---
+
+## Description
+[Falcon](http://inspirehep.net/record/1456803) is an ultra-fast non-parametric detector simulation package that automatically abstracts detector response, usually done by hand in fast-simulators used by particle physics experiments. Falcon uses [KDTrees](https://root.cern.ch/doc/v608/classTKDTreeBinning.html) to build a fast lookup table to map events at the parton shower level to events at the reconstruction level as described in the following [paper](http://inspirehep.net/record/1456803).
+
+The goal of this project is to optimize the structure of the code by using the latest available classes in ROOT. Additionally, the goal is to integrate multi-target regression capability into Falcon. 
+
+## Task ideas and expected results
+  * Optimize Falcon’s design for maximal timing efficiency.
+  * Improve the training and KDTree binning and lookup time by using the latest ROOT classes.
+
+
+## Requirements
+Strong development skills, good knowledge of C++ and Python. Interest in Machine Learning algorithms and applications.
+
+## Mentors 
+  * [Harrison Prosper](mailto:[email protected]?subject=FALCON)
+  * [Sergei Gleyzer](mailto:[email protected]?subject=FALCON)
+  * [Omar Zapata](mailto:[email protected]?subject=FALCON)
+
+## Links
+  * [http://root.cern](http://root.cern)

_gsocproposals/2018/proposal_ROOTmpi.md

@@ -0,0 +1,44 @@
+---
+title: Message Passing Interface for ROOT (ROOTMpi)
+layout: gsoc_proposal
+project: ROOT
+year: 2018
+organization:
+  - OProject
+  - CERN
+  - UdeA
+---
+
+# Description
+
+By standardizing the way different machines communicate during a running process, we can analyze bigger chunks of data in less time. ROOT MPI allows communication of ROOT’s native objects on top of the C/C++ raw data types. ROOT’s serialization methods and optimal design of the new C++ standard permits the user to focus on the algorithm instead of low level syntax.
+
+
+## Task ideas
+ * Extend existing communication schemas.
+ * Write support for MPI files (may consider some design or idea to integrate it to TFile).
+ * Checkpoint support at least in Open MPI and MPICH.
+ * Improve the error handler system and messages in the output.
+ * User tools:
+    * Write a profiling tool support.
+    * Write a benchmarking module.
+    * Integrate valgrind command to ROOTMpi command for debug.
+
+**Expected results**: 
+* Working implementation with tests and documentation.
+* Performance comparison with a basic example between ROOTMpi and Proof. 
+
+**Requirements**: Advanced skills in C/C++, experience in parallel programming with MPI
+
+**Mentors**: 
+  * [Omar Zapata](mailto:[email protected]?subject=ROOTMpi)
+  * [Lorenzo Moneta](mailto:[email protected]?subject=ROOTMpi) 
+  * [Diego Restrepo](mailto:[email protected]?subject=ROOTMpi)
+
+**Links**:
+
+  * [http://root.cern](http://root.cern)
+  * [http://mpi-forum.org](http://mpi-forum.org)
+  * [http://oproject.org/pages/ROOTMpi.html](http://oproject.org/pages/ROOTMpi.html)
+  * [https://root.cern.ch/proof](https://root.cern.ch/proof)
+

_gsocproposals/2018/proposal_TMVACNN.md

@@ -0,0 +1,35 @@
+---
+title: Machine Learning Project - Convolutional Deep Neural Networks on GPUs for Particle Physics Applications
+layout: gsoc_proposal
+project: TMVA
+year: 2018
+organization:
+  - Florida
+  - CERN
+  - OProject
+  - ETH
+  - EPFL
+---
+
+# Description
+
+Toolkit for Multivariate Analysis (TMVA) is a multi-purpose machine learning toolkit integrated into the ROOT scientific software framework, used in many particle physics data analyses and applications. In the past two years we have expanded TMVA’s capabilities to include various deep learning architectures: Fully-connected (DNN), Convolutional (CNN) and Recurrent (RNN) Neural Networks. Currently, only the DNN supports interactive training on GPUs. This summer we would like to expand the GPU implementations to include convolutional and possibly recurrent deep neural networks (CNN and RNN).  Both have very promising applications in particle physics such as particle and event classification, imaging calorimetry and particle tracking, allowing physicists to use new techniques to identify particles and search for new physics.
+
+
+## Task ideas
+ * Production-ready gpu version of the convolutional deep learning library.
+ * Support for GPUs for training.
+
+
+**Requirements**: Strong C++ skills, solid knowledge of deep learning, understanding of convolutional and/or recurrent networks, familiarity with GPU interfaces a plus
+
+**Mentors**: 
+* [Sergei Gleyzer](mailto:[email protected]?subject=TMVA%20CNN) 
+* [Lorenzo Moneta](mailto:[email protected]?subject=TMVA%20CNN) 
+* [Vladimir Ilievski](mailto:[email protected]?subject=TMVA%20CNN)
+* [Saurav Shekhar](mailto:[email protected]?subject=TMVA%20CNN)
+
+**Links**:
+  * [http://root.cern/tmva](http://root.cern/tmva)
+  * [TMVA source code](https://github.com/root-project/root/tree/master/tmva)
+

_gsocproposals/2018/proposal_TMVAGANs.md

@@ -0,0 +1,38 @@
+---
+title: Generative Adversarial Networks for Particle Physics Applications
+layout: gsoc_proposal
+project: TMVA
+year: 2018
+organization:
+  - UdeA
+  - Florida
+  - CERN
+  - KIT
+  - OProject
+---
+
+# Description
+
+The use of Generative Adversarial Networks (GANs) is of particular interest because of potential applications for particle physics in the area of fast detector simulation and reducing the systematic uncertainty related to applying machine learning algorithms. GANs are sets of networks competing with each other. For example, a generator network produces simulated samples based on a training set, competing with a classification network that attempts to classify events. The use of GANs is of particular interest for potential applications focused on fast and accurate event simulation as well as other applications aimed at reducing the dependence of the classifier on specific parameters. 
+
+The Toolkit for Multivariate Analysis (TMVA) is a multi-purpose machine learning toolkit integrated into the ROOT scientific software framework, used in many particle physics data analyses and applications. In the past two years we have expanded TMVA’s capabilities to include robust implementations of various deep learning architectures: Fully-connected (DNN), Convolutional (CNN) and Recurrent (RNN) Neural Networks. 
+
+The goal of this project is to extend the existing deep learning libraries in TMVA to support GANs. 
+
+
+## Task ideas and expected results
+  * Production-ready GAN library.
+  * GPU support for training.
+
+
+**Requirements**: Strong C++ skills, solid knowledge of deep learning, understanding of GANs, familiarity with GPUs
+
+**Mentors**: 
+* [Sergei Gleyzer](mailto:[email protected]?subject=TMVA%20GANs) 
+* [Omar Zapata](mailto:[email protected]?subject=TMVA%20GANs)
+* [Stefan Wunsch](mailto:[email protected]?subject=TMVA%20GANs)
+
+**Links**:
+  * [http://root.cern/tmva](http://root.cern/tmva)
+  * [TMVA source code](https://github.com/root-project/root/tree/master/tmva)
+

_gsocproposals/2018/proposal_TMVATensorFlow.md

@@ -0,0 +1,39 @@
+---
+title: Tensorflow-TMVA Interface
+layout: gsoc_proposal
+project: TMVA
+year: 2018
+organization:
+  - Florida
+  - CERN
+  - KIT
+  - UTA
+---
+
+# Description
+
+TensorFlow is a popular open-source software library for deep learning applications. It supports advanced math and flexible data-flows to build and train powerful deep neural networks.
+
+Toolkit for Multivariate Analysis (TMVA) is a multi-purpose machine learning toolkit integrated into the ROOT scientific software framework, used in many particle physics data analyses and applications.
+
+The goal of this project is to write an interface between TMVA and TensorFlow that allows use of TensorFlow's functionality within TMVA. 
+
+## Task ideas and expected results
+  * Fully-functional interface between Tensorflow and TMVA.
+  * It is important to design an interface that considers various input-data formats for relevant input data types: images, flat files, etc. on both sides.
+
+
+
+**Requirements**: Strong C++ skills, good knowledge of deep learning, familiarity with Tensorflow, familiarity with ROOT and TMVA a plus.
+
+**Mentors**: 
+* [Sergei Gleyzer](mailto:[email protected]?subject=Tensorflow-TMVA%20Interface) 
+* [Fernanda Psihas](mailto:[email protected]?subject=Tensorflow-TMVA%20Interface)
+* [Stefan Wunsch](mailto:[email protected]?subject=Tensorflow-TMVA%20Interface)
+
+
+
+**Links**:
+  * [http://root.cern/tmva](http://root.cern/tmva)
+  * [TMVA source code](https://github.com/root-project/root/tree/master/tmva)
+