BKK16-400B ODPI - Standardizing Hadoop

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The current Hadoop ecosystem is challenged and slowed by fragmented and duplicated efforts. An industry standard is required that translates to immediate benefits that will increase stability, capabilities and compatibility among Hadoop distributions. Its also important to include an open data management core with emphasis on making it enterprise focused. The ODPi is a shared industry effort focused on build such standards and also promoting and advancing the state of Big Data technologies. Linaro is actively involved in this effort and also to make sure ODPi is ARM compatible. This talk will go over some of specifications defined, Linaro's contributions, Roadmap and a quick demo

Tecnologia

Presented by
Date
Event
ODPi (Open Data Platform Initiative)
Ganesh Raju & Naresh Bhat
Big Data Team, LEG
BKK14-400B March 10, 2016
Linaro Connect BKK16
Standardizing Hadoop Ecosystem

Why ODPi ?
● Hadoop is a collection of 47+ components
○ Compatibility issues
○ Insufficient documentation
○ No proper integrated tests
○ Maintenance nightmare
■ Release cycle timelines
■ Api changes
■ Config files
● Help minimize the fragmentation and duplication of effort
within the industry

In the table below, you can see who supports what. Other projects supported by all the vendors include HBase,
Hive, Pig, Spark, and Zookeeper – for a total of 8 projects supported by all. Potential for more.

What is ODPi ?
● A shared industry effort to advance the state of the Apache
Hadoop and Big Data technologies for the enterprise
● Provide a well integrated and tested stable base
● Bringing real enterprise demands to align with the
developer community
● Configuration optimizations
● Best practices and standards
● Platform agnostic (ARM, X86, etc.)
● Certification programs
● Backed by Linux Foundation

Benefits for ISVs
● Eliminates fragmentation, reduces costs, accelerates time to market
○ Cost of maintaining external open source components.
○ Insufficient documentation
● Promotes compatibility between distros.
● Members can focus on innovation and differentiated value-add
● Already companies like Pivotal, Hortonworks, IBM and Altiscale have big
data solutions based on ODPi specs

ODPi Components
● ODPi consists of 2 stacks
○ Runtime stack
○ Management stack
● ODPi currently consists of only 3 components in Runtime stack and Ambari
on the management stack

ODPi - Current status
● Automated CI loop builds are established. Local Nexus repository is setup to store all artifacts
instead of getting from apache
● Utilizing BigTop as single tool for CI build, deployment and automated tests
● Defining more smoke tests.
● Spec for runtime stack is in draft, publically shared
● Working on certification specs for distros
● Technical progress can be found at: https://github.com/odpi
Challenges:
● Concession between members.
● Management tool like Ambari

Linaro is a Member ODPi
● Enablement of AARCH64
● Tested on Member Platforms
● Participate in Technical Spec
● Provide feedback to the community
● Provide Engineering efforts

Linaro’s contribution
● Reference ARM64 build
● Patches to Apache Bigtop
● ODPi tested against multi node ARM based clusters
● Benchmarking and performance tuning for ARM
● JDK optimizations
● ARM based Developer Cloud for ODPi members to set up CI builds and
tests

ODPi Installation and Run Instructions
● ODPi specs can be found here: https://github.com/odpi/specs/blob/v1.0.0-
runtime-draft/ODPi-Operations.md
● ODPi deb and rpm packages can be found on Linaro repositories:
○ Debian Jessie - http://repo.linaro.org/ubuntu/linaro-overlay/
○ CentOS7 - http://repo.linaro.org/rpm/linaro-overlay/centos-7/
● ODPi Installation, setup and instructions to run
○ https://github.com/96boards/documentation/wiki/ODPi-Hadoop-Installation

ODPi Milestones
● RC of spec for runtime stack will be delivered on March
● First official release of ODPi will be by end of March
● Next release will be in October with a cadence of release every 6 months
● Voting procedure to be defined by April to let members choose the next
important component to be added into ODPi (Could be HBase / Hive /
Spark)

ODPi Roadmap
● Add more tests
● Certification program with tests for members to validate against them
● Expanding tests to applications
● Containerize ODPi
● Make ODPi more cloud friendly, make Ambari-like management stack
more cloud integrated
● Grow the footprint and have as many components included as possible

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Speaker: Pavel Shamis Company: Arm Speaker Bio: "Pavel is a Principal Research Engineer at ARM with over 16 years of experience in development HPC solutions. His work is focused on co-design software and hardware building blocks for high-performance interconnect technologies, development communication middleware and novel programming models. Prior to joining ARM, he spent five years at Oak Ridge National Laboratory (ORNL) as a research scientist at Computer Science and Math Division (CSMD). In this role, Pavel was responsible for research and development multiple projects in high-performance communication domain including: Collective Communication Offload (CORE-Direct & Cheetah), OpenSHMEM, and OpenUCX. Before joining ORNL, Pavel spent ten years at Mellanox Technologies, where he led Mellanox HPC team and was one of the key driver in enablement Mellanox HPC software stack, including OFA software stack, OpenMPI, MVAPICH, OpenSHMEM, and other. Pavel is a recipient of prestigious R&D100 award for his contribution in development of the CORE-Direct collective offload technology and he published in excess of 20 research papers. " Talk Title: HPC network stack on ARM Talk Abstract: Applications, programming languages, and libraries that leverage sophisticated network hardware capabilities have a natural advantage when used in today¹s and tomorrow's high-performance and data center computer environments. Modern RDMA based network interconnects provides incredibly rich functionality (RDMA, Atomics, OS-bypass, etc.) that enable low-latency and high-bandwidth communication services. The functionality is supported by a variety of interconnect technologies such as InfiniBand, RoCE, iWARP, Intel OPA, Cray¹s Aries/Gemini, and others. Over the last decade, the HPC community has developed variety user/kernel level protocols and libraries that enable a variety of high-performance applications over RDMA interconnects including MPI, SHMEM, UPC, etc. With the emerging availability HPC solutions based on ARM CPU architecture it is important to understand how ARM integrates with the RDMA hardware and HPC network software stack. In this talk, we will overview ARM architecture and system software stack, including MPI runtimes, OpenSHMEM, and OpenUCX.

HPC network stack on ARM - Linaro HPC Workshop 2018

Linaro

Speaker: Jay Kruemcke Speaker Company: SUSE Bio: "Jay is responsible for the SUSE Linux server products for High Performance Computing, 64-bit ARM systems, and SUSE Linux for IBM Power servers. Jay has built an extensive career in product management including using social media for client collaboration, product positioning, driving future product directions, and evangelizing the capabilities and future directions for dozens of enterprise products. " Talk Title: It just keeps getting better - SUSE enablement for Arm Talk Abstract: SUSE has been delivering commercial Linux support for Arm based servers since 2016. Initially the focus was on high end servers for HPC and Ceph based software defined storage. But we have enabled a number of other Arm SoCs and are even supporting the Raspberry Pi. This session will cover the SUSE products that are available for the Arm platform and view to the future.

It just keeps getting better - SUSE enablement for Arm - Linaro HPC Workshop ...

Linaro

Speakers: Gilad Shainer and Scot Schultz Company: Mellanox Technologies Talk Title: Intelligent Interconnect Architecture to Enable Next Generation HPC Talk Abstract: The latest revolution in HPC interconnect architecture is the development of In-Network Computing, a technology that enables handling and accelerating application workloads at the network level. By placing data-related algorithms on an intelligent network, we can overcome the new performance bottlenecks and improve the data center and applications performance. The combination of In-Network Computing and ARM based processors offer a rich set of capabilities and opportunities to build the next generation of HPC platforms. Gilad Shainer Bio: Gilad Shainer has served as Mellanox's vice president of marketing since March 2013. Previously, Mr. Shainer was Mellanox's vice president of marketing development from March 2012 to March 2013. Mr. Shainer joined Mellanox in 2001 as a design engineer and later served in senior marketing management roles between July 2005 and February 2012. Mr. Shainer holds several patents in the field of high-speed networking and contributed to the PCI-SIG PCI-X and PCIe specifications. Gilad Shainer holds a MSc degree (2001, Cum Laude) and a BSc degree (1998, Cum Laude) in Electrical Engineering from the Technion Institute of Technology in Israel. Scot Schultz Bio: Scot Schultz is a HPC technology specialist with broad knowledge in operating systems, high speed interconnects and processor technologies. Joining the Mellanox team in 2013, Schultz is 30-year veteran of the computing industry. Prior to joining Mellanox, he spent the past 17 years at AMD in various engineering and leadership roles in the area of high performance computing. Scot has also been instrumental with the growth and development of various industry organizations including the Open Fabrics Alliance, and continues to serve as a founding board-member of the OpenPOWER Foundation and Director of Educational Outreach and founding member of the HPC-AI Advisory Council.

Intelligent Interconnect Architecture to Enable Next Generation HPC - Linaro ...

Linaro

Yutaka Ishikawa - Post-K and Arm HPC Ecosystem - Linaro Arm HPC Workshop Santa Clara 2018 Bio: "Yutaka Ishikawa is the project leader of developing the post K supercomputer. From 1987 to 2001, he was a member of AIST (former Electrotechnical Laboratory), METI. From 1993 to 2001, he was the chief of Parallel and Distributed System Software Laboratory at Real World Computing Partnership. He led development of cluster system software called SCore, which was used in several large PC cluster systems around 2004. From 2002 to 2014, he was a professor at the University Tokyo. He led a project to design a commodity-based supercomputer called T2K open supercomputer. As a result, three universities, Tsukuba, Tokyo, and Kyoto, obtained each supercomputer based on the specification in 2008. He was also involved with the design of the Oakleaf-PACS, the successor of T2K supercomputer in both Tsukuba and Tokyo, whose peak performance is 25PF." Session Title: Post-K and Arm HPC Ecosystem Session Description: "Post-K, a flagship supercomputer in Japan, is being developed by Riken and Fujitsu. It will be the first supercomputer with Armv8-A+SVE. This talk will give an overview of Post-K and how RIKEN and Fujitsu are currently working on software stack for an Arm architecture."

Yutaka Ishikawa - Post-K and Arm HPC Ecosystem - Linaro Arm HPC Workshop Sant...

Linaro

Event: Arm Architecture HPC Workshop by Linaro and HiSilicon Location: Santa Clara, CA Speaker: Andrew J Younge Talk Title: Vanguard Astra - Petascale Arm Platform for U.S. DOE/ASC Supercomputing Talk Desc: The Vanguard program looks to expand the potential technology choices for leadership-class High Performance Computing (HPC) platforms, not only for the National Nuclear Security Administration (NNSA) but for the Department of Energy (DOE) and wider HPC community. Specifically, there is a need to expand the supercomputing ecosystem by investing and developing emerging, yet-to-be-proven technologies and address both hardware and software challenges together, as well as to prove-out the viability of such novel platforms for production HPC workloads. The first deployment of the Vanguard program will be Astra, a prototype Petascale Arm supercomputer to be sited at Sandia National Laboratories during 2018. This talk will focus on the arthictecural details of Astra and the significant investments being made towards the maturing the Arm software ecosystem. Furthermore, we will share initial performance results based on our pre-general availability testbed system and outline several planned research activities for the machine. Bio: Andrew Younge is a R&D Computer Scientist at Sandia National Laboratories with the Scalable System Software group. His research interests include Cloud Computing, Virtualization, Distributed Systems, and energy efficient computing. Andrew has a Ph.D in Computer Science from Indiana University, where he was the Persistent Systems fellow and a member of the FutureGrid project, an NSF-funded experimental cyberinfrastructure test-bed. Over the years, Andrew has held visiting positions at the MITRE Corporation, the University of Southern California / Information Sciences Institute, and the University of Maryland, College Park. He received his Bachelors and Masters of Science from the Computer Science Department at Rochester Institute of Technology (RIT) in 2008 and 2010, respectively.

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1. Presented by Date Event ODPi (Open Data Platform Initiative) Ganesh Raju & Naresh Bhat Big Data Team, LEG BKK14-400B March 10, 2016 Linaro Connect BKK16 Standardizing Hadoop Ecosystem

2. Why ODPi ? ● Hadoop is a collection of 47+ components ○ Compatibility issues ○ Insufficient documentation ○ No proper integrated tests ○ Maintenance nightmare ■ Release cycle timelines ■ Api changes ■ Config files ● Help minimize the fragmentation and duplication of effort within the industry

3. In the table below, you can see who supports what. Other projects supported by all the vendors include HBase, Hive, Pig, Spark, and Zookeeper – for a total of 8 projects supported by all. Potential for more.

4. What is ODPi ? ● A shared industry effort to advance the state of the Apache Hadoop and Big Data technologies for the enterprise ● Provide a well integrated and tested stable base ● Bringing real enterprise demands to align with the developer community ● Configuration optimizations ● Best practices and standards ● Platform agnostic (ARM, X86, etc.) ● Certification programs ● Backed by Linux Foundation

5. Benefits for ISVs ● Eliminates fragmentation, reduces costs, accelerates time to market ○ Cost of maintaining external open source components. ○ Insufficient documentation ● Promotes compatibility between distros. ● Members can focus on innovation and differentiated value-add ● Already companies like Pivotal, Hortonworks, IBM and Altiscale have big data solutions based on ODPi specs

7. ODPi Components ● ODPi consists of 2 stacks ○ Runtime stack ○ Management stack ● ODPi currently consists of only 3 components in Runtime stack and Ambari on the management stack

8. ODPi - Current status ● Automated CI loop builds are established. Local Nexus repository is setup to store all artifacts instead of getting from apache ● Utilizing BigTop as single tool for CI build, deployment and automated tests ● Defining more smoke tests. ● Spec for runtime stack is in draft, publically shared ● Working on certification specs for distros ● Technical progress can be found at: https://github.com/odpi Challenges: ● Concession between members. ● Management tool like Ambari

9. Linaro is a Member ODPi ● Enablement of AARCH64 ● Tested on Member Platforms ● Participate in Technical Spec ● Provide feedback to the community ● Provide Engineering efforts

10. Linaro’s contribution ● Reference ARM64 build ● Patches to Apache Bigtop ● ODPi tested against multi node ARM based clusters ● Benchmarking and performance tuning for ARM ● JDK optimizations ● ARM based Developer Cloud for ODPi members to set up CI builds and tests

11. ODPi Installation and Run Instructions ● ODPi specs can be found here: https://github.com/odpi/specs/blob/v1.0.0- runtime-draft/ODPi-Operations.md ● ODPi deb and rpm packages can be found on Linaro repositories: ○ Debian Jessie - http://repo.linaro.org/ubuntu/linaro-overlay/ ○ CentOS7 - http://repo.linaro.org/rpm/linaro-overlay/centos-7/ ● ODPi Installation, setup and instructions to run ○ https://github.com/96boards/documentation/wiki/ODPi-Hadoop-Installation

12. ODPi Milestones ● RC of spec for runtime stack will be delivered on March ● First official release of ODPi will be by end of March ● Next release will be in October with a cadence of release every 6 months ● Voting procedure to be defined by April to let members choose the next important component to be added into ODPi (Could be HBase / Hive / Spark)

13. ODPi Roadmap ● Add more tests ● Certification program with tests for members to validate against them ● Expanding tests to applications ● Containerize ODPi ● Make ODPi more cloud friendly, make Ambari-like management stack more cloud integrated ● Grow the footprint and have as many components included as possible

14. Demo By Naresh Bhat

15. Q & A

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