Lobster Talk at Condor Week 2015

Ben Tovar gave an overview of Lobster in the talk High-Energy Physics workloads on 10k non-dedicated opportunistic cores with Lobster. The talk was part of Condor Week 2015, at the University of Wisconsin-Madison.

Lobster is a system for deploying data intensive high-throughput science applications on non-dedicated resources. It is build on top Work Queue, Parrot, and Chirp, which are part of CCTools.

Parrot and Lobster at CHEP 2015

CCL students gave two poster presentations at the annual Computing in High Energy Physics (CHEP) conference in Japan.  Both represent our close collaboration with the CMS HEP group at Notre Dame:


Haiyan Meng presented A Case Study in Preserving a High Energy Physics Application.  This poster describes the complexity of preserving a non-trivial application, the shows how Parrot packaging technology can be used to capture a program's
dependencies, and then re-execute it using a variety of technologies.





Anna Woodard and Matthias Wolf won the best poster presentation award for Exploiting Volatile Opportunistic Computing Resources with Lobster, which was rewarded with a lightning plenary talk.  Lobster is an analysis workload management system which has been able to harness 10-20K opportunistic cores at a time for large workloads at Notre Dame, making the facility comparable in size to the dedicated Tier-2 facilities of the WLCG!

Peter Sempolinski Defends Ph.D.

Dr. Peter Sempolinski successfully defended his PhD thesis titled "An Extensible System for Facilitating Collaboration for Structural Engineering Applications"

While at Notre Dame, Peter created a Virtual Wind Tunnel which enabled the crowdsourcing of structural design and evaluation by combining online building design with Google Sketchup and CFD simulation with OpenFoam.  The system was used in a variety of contexts, ranging from virtual engineering classes to managing work crowdsourced via Mechanical Turk. his work was recently accepted for publication in IEEE CiSE and PLOS1.

Congratulations to Dr. Sempolinski!

CMS Analysis on 10K Cores with Lobster

The CMS physics group at Notre Dame has created Lobster, a data analysis system that runs on O(10K) cores to process data produced by the CMS experiment at the LHC.  Lobster uses Work Queue to dispatch tasks to thousands of machines, Parrot with CVMFS to deliver the complex software stack from CERN, XRootD to deliver the LHC data, and Chirp and Hadoop to manage the output data. By using these technologies, Lobster is able to harness arbitrary machines and bring along the CMS computing environment wherever it goes.   At peak, Lobster at ND delivers capacity equal to that of a dedicated CMS Tier-2 facility!     (read more here)

Dinesh Rajan Defends Ph.D.

Dr. Dinesh Rajan successfully defended his PhD thesis titled "Principles for the Design and Operating of Elastic Scientific Applications on Distributed Systems"  He is currently an engineer at Amazon Web Services.

While at Notre Dame, hd made significant contributions to the development of Work Queue and worked closely with scientists in biology and molecular dynamics to build highly scalable elastic applications such as the Accelerated Weighted Ensemble.  His most recent journal paper in IEEE TCC describes how to design self-tuning cloud applications.

Congratulations to Dr. Rajan!

Confuga: Scalable Data Intensive Computing for POSIX Workflows

Patrick Donnely will present his work on the Confuga distributed filesystem at  CCGrid 2015 in China:

Patrick Donnelly, Nicholas Hazekamp, Douglas Thain,Confuga: Scalable Data Intensive Computing for POSIX Workflows, IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May, 2015.  

Confuga is a new active storage cluster file system designed for executing regular POSIX workflows. Users may store extremely large datasets on Confuga in a regular file system layout, with whole files replicated across the cluster. You may then operate on your dataset using regular POSIX applications, with defined inputs and outputs.

Confuga handles the details of placing jobs near data and minimizing network load so that the cluster's disk and network resources are used efficiently. Each job executes with all of its input file dependencies local to its execution, within a sandbox.

For those familiar with CCTools, Confuga operates as a cluster of Chirp servers with a single Chirp server operating as the head node. You may use the Chirp library, Chirp CLI toolset, FUSE, or even Parrot to upload and manipulate the data on Confuga.

For running a workflow on Confuga, we encourage you to use Makeflow. Makeflow will submit the jobs to Confuga using the Chirp job protocol and take care of ordering the jobs based on their dependencies.

Makeflow Visualization with Cytoscape

We have created a new Makeflow visualization module which exports a workflow into an xgmml file compatible with Cytoscape.  Cytoscape is a powerful network graphing application with support for custom styles, layouts, annotations, and more. While this program is known more for visualizing molecular networks in biology, it can be used for any purpose, and we believe it is a powerful tool for visualizing makeflow tasks.  Our visualization module was designed for and tested on Cytoscape 3.2. The following picture is a Cytoscape visualization of the example makeflow script provided in the User’s Manual (http://ccl.cse.nd.edu/software/manuals/makeflow.html):

To generate a Cytoscape graph from your makeflow script, simply run:

makeflow_viz –D cytoscape workflow.mf > workflow.xgmml

 workflow.xgmml can then be opened in Cytoscape through File -> Import -> Network -> File.  We have created a clean style named specifically for visualizing makeflow tasks named style.xml, which is generated in the present working directory when you run makeflow_viz. To apply the style in Cytoscape, select File -> Import -> Style, and select the style.xml file.  Next, right-click the imported network and select “Apply Style…”.  Select “makeflow” from the dropdown menu and our style will be applied.  This will add the proper colors, edges, arrows, and shapes for processes and files.

Cytoscape also has a built in layout function which can be used to automatically rearrange nodes according to their hierarchy.   To access this, select Layout à Settings, and a new window will pop up.  Simply select “Hierarchical Layout” from the dropdown menu, change the settings for that layout to your liking, and select “Execute Layout.”  There is a caveat with this function.  With larger makeflow tasks, this auto layout function can take long to complete.   This is due to Cytoscape being designed for all types of graphs, and they do not appear to implement algorithms specifically for dags to take advantage of faster time complexities.  We have tested the auto-layout function with the following test cases:

Number of nodes	Number of edges	Time to layout nodes
114	258	20-30 seconds
2213	11526	2.5 hours
15245	30478	23 hours

After the layout completes, the graph should be visible in a clean fashion, and you can customize the display further to your liking with the various options available in Cytoscape.  For more information about Cytoscape, visit http://cytoscape.org

Creating Better Force Fields on Distributed GPUs with Work Queue

ForceBalance is an open source software tool for creating accurate force fields for molecular mechanics simulation using flexible combinations of reference data from experimental measurements and theoretical calculations. These force fields are used to simulate the dynamics and physical properties of molecules in chemistry and biochemistry.

The Work Queue framework gives ForceBalance the ability to distribute computationally intensive components of a force field optimization calculation in a highly flexible way. For example, each optimization cycle launched by ForceBalance may require running 50 molecular dynamics simulations, each of which may take 10-20 hours on a high end NVIDIA GPU. While GPU computing resources are available, it is rare to find 50 available GPU nodes on any single supercomputer or HPC cluster. With Work Queue, it is possible to distribute the simulations across several HPC clusters, including the Certainty HPC cluster at Stanford, the Keeneland GPU cluster managed by Georgia Tech and Oak Ridge National Laboratories, and the Stampede supercomputer managed by the University of Texas. This makes it possible to run many simulations in parallel and complete the high level optimization in weeks instead of years.

 - Lee-Ping Wang, Stanford University

CCTools 4.3 released

The Cooperative Computing Lab is pleased to announce the release of version 4.3.0 of the Cooperative Computing Tools, including Parrot, Chirp, Makeflow, WorkQueue, Weaver, DeltaDB, SAND, All-Pairs, and other software. This release has some important changes:

• Peter Bui's Weaver is included. Weaver is a high level interface to Makeflow which allows to describe workflows using python. For more information see cctools/doc/man/weaver.1 and cctools/weaver/examples in the distribution.
• This is also the first release to include DeltaDB, written by Peter Ivie and Douglas Thain. DeltaDB implements a model for time-varying schema-free data and underlies the query engine for the CCTools catalog server.
• Backwards compatibility of master and workers pre-4.3 is broken. Workers from 4.3 cannot connect to masters pre-4.3, and masters from 4.3 will not accept connection from workers pre-4.3. The API did not change, thus unless you want to take advantage of new features, you should not need to modify your code.
• The interface to work_queue_pool has been simplified, and all options have to be specified at the command line. Please see cctools/doc/man/work_queue_pool.1 for more information.
• Undefined environment variables used in Makeflow are no longer allowed by the parser.
• Binaries for 32bit architectures are not being distributed as part of this release. Please let us know if you need them.

Other highlights

• [WorkQueue] Perl object oriented bindings have been added. See perldoc Work_Queue::Queue [B. Tovar]
• [WorkQueue] A priority per task can now be specified. [D. Thain, B. Tovar]
• [WorkQueue] --single-shot option added to workers to exit quickly after the master disconnects [D. Thain].
• [WorkQueue] Hierarchy statistics when using foremen are now available. [B. Tovar, M. Wolf]
• [WorkQueue] work_queue_pool code cleanup. [D. Thain, B. Tovar]
• [Makeflow] New lexer and parser with cleaner semantics and error reporting. [B. Tovar]
• [Parrot] Bug fix that allows parrot's temp-dir to be on GPFS. [P. Donnelly]
• [Parrot] Several fixes to better support executables with threads. [P. Donnelly]
• [Parrot] Update to use the newer ptrace API. [P. Donnelly]
• [Parrot] Several updates to parrot_package_run. See cctools/doc/man/parrot_package_run. [H. Meng]
• [Parrot] iRODS 4.x support. [D. Thain]

You can download the software here: cctools download

Thanks goes to the contributors and testers for this release: Peter Bui, Patrick Donnelly, Nick Hazekamp, Peter Ivie, Kangkang Li, Haiyan Meng, Peter Sempolinski, Douglas Thain, Ben Tovar, Lee-Ping Wang, Matthias Wolf, Anna Woodard, and Charles Zheng

Enjoy!

Work Queue Powers Nanoreactor Simulations

Lee-Ping Wang at Stanford University, recently published a paper in Nature Chemistry describing his work in fundamental molecular dynamics.

The paper demonstrates the "nanoreactor" technique in which simple molecules are simulated over a long time scale to observe their reaction paths into more complex molecules.  For example, the picture below shows 39 Acetylene molecules merging into a variety of hydrocarbons over the course of 500ps simulated time.  This technique can be used to computationally predict reaction networks in historical or inaccessible environments, such as the early Earth or the upper atmosphere.

To compute the final reaction network for this figure, the team used the Work Queue framework to harness over 300K node-hours of CPU time on the Blue Waters supercomputer at NCSA.