A Podcast for HPC Folk

A Podcast for HPC Folk

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RCE 106: Singularity


Brock Palen and Jeff Squyres speak with Gregory Kurtzer about Singularity a container solution for HPC and research environments. Singularity allows a non-privileged user to "swap out" the operating system on the host for one they control. So if the host system is running RHEL6 but your application runs in Ubuntu, you can create an Ubuntu image, install your applications into that image, copy the image to another host, and run your application on that host in it's native Ubuntu environment.

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Gregory Kurtzer has created many open source initiatives related to HPC namely: Centos Linux, Warewulf, Perceus, and most recently Singularity. Currently Gregory serves as a member of the OpenHPC Technical Steering Committee and is the IT HPC Systems Architect and Software Developer for Lawrence Berkeley National Laboratory.

RCE 105: Impala


Brock Palen and Jeff Squyres speak with Marcel Kornacker about Impala. Impala brings scalable parallel database technology to Hadoop, enabling users to issue low-latency SQL queries to data stored in HDFS and Apache HBase without requiring data movement or transformation. Impala is integrated with Hadoop to use the same file and data formats, metadata, security and resource management frameworks used by MapReduce, Apache Hive, Apache Pig and other Hadoop software.

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Marcel Kornacker is the Chief Architect for database technology at Cloudera and creator of the Cloudera Impala project. Following his graduation in 2000 with a PhD in databases from UC Berkeley, he held engineering positions at several database-related start-up companies. Marcel joined Google in 2003 where he worked on several ads serving and storage infrastructure projects, then became tech lead for the distributed query engine component of Google's F1 project.

RCE 104: D-Wave Quantum Computing


Brock Palen and Jeff Squyres speak with Denny Dahl about D-Wave and Quantum Computing. Founded in 1999, D-Wave Systems is the world's first quantum computing company. Our mission is to integrate new discoveries in physics, engineering, manufacturing, and computer science into breakthrough approaches to computation that help solve some of the world’s most complex challenges.

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Edward (Denny) Dahl is a Ph.D. physicist who has been at D-Wave Systems for over four years. He works with customers to help them understand the principles of adiabatic quantum computing as implemented in the D-Wave 2X System. He is currently on assignment at the Los Alamos National Laboratory, which recently purchased a one-thousand qubit system from D-Wave. His interests are quantum programming, playing the guitar and exploring the high deserts of north central New Mexico.

RCE 103: EasyBuild


Brock Palen and Jeff Squyres speak with Kenneth Hoste about EasyBuild. EasyBuild is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.

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Kenneth Hoste received his Masters degree and Ph.D in Computer Science from Ghent University in Belgium in 2005 and 2010, respectively. His research topic consisted of applying machine learning techniques to various problems that relate to analysis, estimation and optimization of computer system performance. Particular topics include the characterization of microarchitecture-independent workload behavior, and applying evolutionary search algorithms to optimizing static and JiT compilers.

Since October 2010, he has been working in the HPC support team of Ghent University, focusing on user support topics. As a direct result of this, he has taken up the role as main developer and release manager of EasyBuild, a community-powered framework written in Python that aims to tackle the ubiquitous problem of automating the tedious task of building and installing (scientific) software.

RCE 102: Spack


Brock Palen and Jeff Squyres speak with Todd Gamblin about Spack. Spack is a package management tool designed to support multiple versions and configurations of software on a wide variety of platforms and environments. It was designed for large supercomputing centers, where many users and application teams share common installations of software on clusters with exotic architectures, using libraries that do not have a standard ABI. Spack is non-destructive: installing a new version does not break existing installations, so many configurations can coexist on the same system.

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Todd is a computer scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory . His research focuses on scalable tools for measuring, analyzing, and visualizing performance the performance of massively parallel simulations. Todd works closely with production simulation teams at LLNL, and he likes to create tools that users can pick up easily.

Frustrated with the complexity of building HPC performance tools, Todd started developing Spack two years ago to allow users to painlessly install software on big machines. Spack has since been adopted by Livermore Computing, other HPC centers, and LLNL application teams. The open source project now includes several core developers at LLNL and a rapidly growing community on GitHub. A 1.0 release is coming soon.

RCE 101: Conduit

Brock Palen and Jeff Squyres speak with Cyrus Harrison about the Conduit an open source project from Lawrence Livermore National Laboratory. It provides an intuitive model for describing hierarchical scientific data in C++, C, Fortran, and Python and is used for data coupling between packages in-core, serialization, and I/O tasks.

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Cyrus is a computer scientist and group leader in the Applications, Simulations, and Quality (ASQ) division of LLNL's Computation directorate. He is the software architect of the VisIt open source visualization tool and leads major aspects of the technical direction of the project. Cyrus also provides custom data analysis solutions for large scale scientific simulations in WCI's WSC and WPD programs.

RCE 100: Fasterdata

Brock Palen and Jeff Squyres speak with Eli Dart about the Fasterdata effort to document ways to make better use of networks for scientific uses.

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The Fasterdata Knowledge Base provides proven, operationally sound methods for troubleshooting and solving performance issues. For over 25 years, ESnet has operated an advanced research network with the goal of enabling the highest levels of performance for the Department of Energy (DOE) scientific community. During this time, our engineers have identified a common set of issues that hinder performance and we would like to share our experiences and findings in this knowledge base.

Eli Dart is a network engineer in the ESnet Science Engagement Group, which seeks to use advanced networking to improve scientific productivity and science outcomes for the DOE science facilities, their users, and their collaborators. Eli is a primary advocate for the Science DMZ design pattern, and works with facilities, laboratories, universities, science collaborations, and science programs to deploy data-intensive science infrastructure based on the Science DMZ model. Eli also runs the ESnet network requirements program, which collects, synthesizes, and aggregates the networking needs of the science programs ESnet serves.

Eli has over 15 years of experience in network architecture, design, engineering, performance, and security in scientific and research environments. His primary professional interests are high-performance architectures and effective operational models for networks that support scientific missions, and building collaborations to bring about the effective use of high-performance networks by science projects.

As a member of ESnet's Network Engineering Group, Eli was a primary contributor to the design and deployment of two iterations of the ESnet backbone network - ESnet4 and ESnet5. Prior to ESnet Eli was a lead network engineer at NERSC, DOE's primary supercomputing facility, where he co-led a complete redesign and several years of successful operation of the high-performance network infrastructure there. In addition, Eli spent 14 years as a member of SCinet, the group of volunteers that builds and operates the network for the annual IEEE/ACM Supercomputing conference series, from 1997 through 2010. He served as Network Security Chair for SCinet for the 2000 and 2001 conferences and was a member of the SCinet routing group from 2001 through 2010. Eli holds a Bachelor of Science degree in Computer Science from the Oregon State University College of Engineering.

RCE 99: perfSONAR

Brock Palen and Jeff Squyres speak with Jason Zurawski about perfSONAR, a network measurement toolkit designed to provide federated coverage of paths, and help to establish end-to-end usage expectations.

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Jason Zurawski is a Science Engagement Engineer at the Energy Sciences Network (ESnet) in the Scientific Networking Division of the Computing Sciences Directorate of the Lawrence Berkeley National Laboratory. ESnet is the high performance networking facility of the US Department of Energy Office of Science. ESnet''s mission is to enable those aspects of the DOE Office of Science research mission that depend on high performance networking for success.

Jason's primary responsibilities include working with members of the research community to identify the roll of networking in scientific workflows, evaluate current requirements, and suggest improvements for future innovations. Jason's professional interests include network monitoring and performance measurement, high performance computing, grid computing, and application development. He is a founding member of several open source R&E software developments, including perfSONAR, OWAMP, BWCTL, NDT, and OSCARS.

Jason has worked in computing and networking since 2007, and has a B.S. in Computer Science & Engineering from The Pennsylvania State University earned in 2002, and an M.S. in Computer and Information Science from The University of Delaware earned in 2007. He has previously worked for the University of Delaware and Internet2. Jason resides and works in the Washington DC metro area, and may be reached via email at This email address is being protected from spambots. You need JavaScript enabled to view it..

RCE 98: Spark

Brock Palen and Jeff Squyres speak with Matei Zaharia about Apache Spark, a fast and general engine for large-scale data processing.

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Matei Zaharia is an assistant professor of computer science at MIT and CTO of Databricks, the company commercializing Apache Spark. He begun the Spark project at UC Berkeley and continues to do research in big data processing and computer systems. Apart from Spark, he has contributed to other open source projects including Apache Mesos, the SNAP sequence aligner, and Apache Hadoop.

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