In this deck from the 2014 HPC User Forum in Seattle, Ed Turkel from HP presents an update on HPC at HP.
Watch the video presentation: http://wp.me/p3RLHQ-d9X
Forrester predicts, CIOs who are late to the Hadoop game will finally make the platform a priority in 2015. Hadoop has evolved as a must-to-know technology and has been a reason for better career, salary and job opportunities for many professionals.
The MapReduce model has become an important parallel processing model for large- scale data-intensive applications like data mining and web indexing. Hadoop, an open-source implementation of MapReduce, is widely applied to support cluster computing jobs requiring low response time. The current Hadoop implementation assumes that computing nodes in a cluster are homogeneous in nature. Data locality has not been taken into account for launching speculative map tasks, because it is assumed that most map tasks can quickly access their local data. Network delays due to data movement during running time have been ignored in the recent Hadoop research. Unfortunately, both the homogeneity and data locality assumptions in Hadoop are optimistic at best and unachievable at worst, potentially introducing performance problems in virtualized data centers. We show in this dissertation that ignoring the data-locality issue in heterogeneous cluster computing environments can noticeably reduce the performance of Hadoop. Without considering the network delays, the performance of Hadoop clusters would be significatly downgraded. In this dissertation, we address the problem of how to place data across nodes in a way that each node has a balanced data processing load. Apart from the data placement issue, we also design a prefetching and predictive scheduling mechanism to help Hadoop in loading data from local or remote disks into main memory. To avoid network congestions, we propose a preshuffling algorithm to preprocess intermediate data between the map and reduce stages, thereby increasing the throughput of Hadoop clusters. Given a data-intensive application running on a Hadoop cluster, our data placement, prefetching, and preshuffling schemes adaptively balance the tasks and amount of data to achieve improved data-processing performance. Experimental results on real data-intensive applications show that our design can noticeably improve the performance of Hadoop clusters. In summary, this dissertation describes three practical approaches to improving the performance of Hadoop clusters, and explores the idea of integrating prefetching and preshuffling in the native Hadoop system.
Near real-time, big data analytics is a reality via a new data pattern that avoids the latency and overhead of legacy ETL–the 3 T’s of Hadoop: Transfer, Transform, and Translate. Transfer: Once a Hadoop infrastructure is in place, a mandate is needed to immediately and continuously transfer all enterprise data, from external and internal sources and through different existing systems, into Hadoop. Previously, enterprise data was isolated, disconnected and monolithically segmented. Through this T, various source data are consolidated and centralized in Hadoop almost as they are generated in near real-time. Transform: Most of the enterprise data, when flowing into Hadoop, is transactional in nature. Analytics requires data be transformed from record-based OLTP form to column-based OLAP. This T is not the same T in ETL as we need to retain the granularity in the data feeds. The key is to transform in-place within Hadoop, without further data movement from Hadoop to other legacy systems. Translate: We pre-compute or provide on-the-fly views of analytical data, exposed for consumption. We facilitate analysis and reporting, for both scheduled and ad hoc needs, to be interactive with the data for analysts and end users, integrated in and on top of Hadoop.
Pivotal: Hadoop for Powerful Processing of Unstructured Data for Valuable Ins...EMC
Pivotal has setup and operationalized 1000 node Hadoop cluster called the Analytics Workbench. It takes special setup and skills to manage such a large deployment. This session shares how we set it up and how you will manage it.
Objective 1: Understand what it takes to operationalize a 1000-nodeHadoop cluster.
After this session you will be able to:
Objective 2: Understand how to set up and manage the day to day challenges of a large Hadoop deployments.
Objective 3: Have a view to the tools that are necessary to solve the challenges of managing the large Hadoop cluster.
Introduction to MapReduce | MapReduce Architecture | MapReduce FundamentalsSkillspeed
This Hadoop MapReduce tutorial will unravel MapReduce Programming, MapReduce Commands, MapReduce Fundamentals, Driver Class, Mapper Class, Reducer Class, Job Tracker & Task Tracker.
At the end, you'll have a strong knowledge regarding Hadoop MapReduce Basics.
PPT Agenda:
✓ Introduction to BIG Data & Hadoop
✓ What is MapReduce?
✓ MapReduce Data Flows
✓ MapReduce Programming
----------
What is MapReduce?
MapReduce is a programming framework for distributed processing of large data-sets via commodity computing clusters. It is based on the principal of parallel data processing, wherein data is broken into smaller blocks rather than processed as a single block. This ensures a faster, secure & scalable solution. Mapreduce commands are based in Java.
----------
What are MapReduce Components?
It has the following components:
1. Combiner: The combiner collates all the data from the sample set based on your desired filters. For example, you can collate data based on day, week, month and year. After this, the data is prepared and sent for parallel processing.
2. Job Tracker: This allocates the data across multiple servers.
3. Task Tracker: This executes the program across various servers.
4. Reducer: It will isolate the desired output from across the multiple servers.
----------
Applications of MapReduce
1. Data Mining
2. Document Indexing
3. Business Intelligence
4. Predictive Modelling
5. Hypothesis Testing
----------
Skillspeed is a live e-learning company focusing on high-technology courses. We provide live instructor led training in BIG Data & Hadoop featuring Realtime Projects, 24/7 Lifetime Support & 100% Placement Assistance.
Email: sales@skillspeed.com
Website: https://www.skillspeed.com
John Sing's Edge 2013 presentation, detailing when/where/how external storage products and/or system software (i.e. GPFS) can be effectively used in a Hadoop storage environment. Many Hadoop situations absolutely required direct attached storage. However, there are many intelligent situations where shared external storage may make sense in a Hadoop environment. This presentation details how/why/where, and promotes taking an intelligent, Hadoop-aware approach to deciding between internal storage and external shared storage. Having full awareness of Hadoop considerations is essential to selecting either internal or external shared storage in Hadoop environment.
At the Virtual HPC User Forum Special Event, Dr. Gene Cooperman explains why Checpoint-Restarts are needed, the development of Distributed MultiThreaded CheckPointing (DMTC), and how persistent memory will help make DMTC practical to implement.
In this deck from the 2014 HPC User Forum in Seattle, Ed Turkel from HP presents an update on HPC at HP.
Watch the video presentation: http://wp.me/p3RLHQ-d9X
Forrester predicts, CIOs who are late to the Hadoop game will finally make the platform a priority in 2015. Hadoop has evolved as a must-to-know technology and has been a reason for better career, salary and job opportunities for many professionals.
The MapReduce model has become an important parallel processing model for large- scale data-intensive applications like data mining and web indexing. Hadoop, an open-source implementation of MapReduce, is widely applied to support cluster computing jobs requiring low response time. The current Hadoop implementation assumes that computing nodes in a cluster are homogeneous in nature. Data locality has not been taken into account for launching speculative map tasks, because it is assumed that most map tasks can quickly access their local data. Network delays due to data movement during running time have been ignored in the recent Hadoop research. Unfortunately, both the homogeneity and data locality assumptions in Hadoop are optimistic at best and unachievable at worst, potentially introducing performance problems in virtualized data centers. We show in this dissertation that ignoring the data-locality issue in heterogeneous cluster computing environments can noticeably reduce the performance of Hadoop. Without considering the network delays, the performance of Hadoop clusters would be significatly downgraded. In this dissertation, we address the problem of how to place data across nodes in a way that each node has a balanced data processing load. Apart from the data placement issue, we also design a prefetching and predictive scheduling mechanism to help Hadoop in loading data from local or remote disks into main memory. To avoid network congestions, we propose a preshuffling algorithm to preprocess intermediate data between the map and reduce stages, thereby increasing the throughput of Hadoop clusters. Given a data-intensive application running on a Hadoop cluster, our data placement, prefetching, and preshuffling schemes adaptively balance the tasks and amount of data to achieve improved data-processing performance. Experimental results on real data-intensive applications show that our design can noticeably improve the performance of Hadoop clusters. In summary, this dissertation describes three practical approaches to improving the performance of Hadoop clusters, and explores the idea of integrating prefetching and preshuffling in the native Hadoop system.
Near real-time, big data analytics is a reality via a new data pattern that avoids the latency and overhead of legacy ETL–the 3 T’s of Hadoop: Transfer, Transform, and Translate. Transfer: Once a Hadoop infrastructure is in place, a mandate is needed to immediately and continuously transfer all enterprise data, from external and internal sources and through different existing systems, into Hadoop. Previously, enterprise data was isolated, disconnected and monolithically segmented. Through this T, various source data are consolidated and centralized in Hadoop almost as they are generated in near real-time. Transform: Most of the enterprise data, when flowing into Hadoop, is transactional in nature. Analytics requires data be transformed from record-based OLTP form to column-based OLAP. This T is not the same T in ETL as we need to retain the granularity in the data feeds. The key is to transform in-place within Hadoop, without further data movement from Hadoop to other legacy systems. Translate: We pre-compute or provide on-the-fly views of analytical data, exposed for consumption. We facilitate analysis and reporting, for both scheduled and ad hoc needs, to be interactive with the data for analysts and end users, integrated in and on top of Hadoop.
Pivotal: Hadoop for Powerful Processing of Unstructured Data for Valuable Ins...EMC
Pivotal has setup and operationalized 1000 node Hadoop cluster called the Analytics Workbench. It takes special setup and skills to manage such a large deployment. This session shares how we set it up and how you will manage it.
Objective 1: Understand what it takes to operationalize a 1000-nodeHadoop cluster.
After this session you will be able to:
Objective 2: Understand how to set up and manage the day to day challenges of a large Hadoop deployments.
Objective 3: Have a view to the tools that are necessary to solve the challenges of managing the large Hadoop cluster.
Introduction to MapReduce | MapReduce Architecture | MapReduce FundamentalsSkillspeed
This Hadoop MapReduce tutorial will unravel MapReduce Programming, MapReduce Commands, MapReduce Fundamentals, Driver Class, Mapper Class, Reducer Class, Job Tracker & Task Tracker.
At the end, you'll have a strong knowledge regarding Hadoop MapReduce Basics.
PPT Agenda:
✓ Introduction to BIG Data & Hadoop
✓ What is MapReduce?
✓ MapReduce Data Flows
✓ MapReduce Programming
----------
What is MapReduce?
MapReduce is a programming framework for distributed processing of large data-sets via commodity computing clusters. It is based on the principal of parallel data processing, wherein data is broken into smaller blocks rather than processed as a single block. This ensures a faster, secure & scalable solution. Mapreduce commands are based in Java.
----------
What are MapReduce Components?
It has the following components:
1. Combiner: The combiner collates all the data from the sample set based on your desired filters. For example, you can collate data based on day, week, month and year. After this, the data is prepared and sent for parallel processing.
2. Job Tracker: This allocates the data across multiple servers.
3. Task Tracker: This executes the program across various servers.
4. Reducer: It will isolate the desired output from across the multiple servers.
----------
Applications of MapReduce
1. Data Mining
2. Document Indexing
3. Business Intelligence
4. Predictive Modelling
5. Hypothesis Testing
----------
Skillspeed is a live e-learning company focusing on high-technology courses. We provide live instructor led training in BIG Data & Hadoop featuring Realtime Projects, 24/7 Lifetime Support & 100% Placement Assistance.
Email: sales@skillspeed.com
Website: https://www.skillspeed.com
John Sing's Edge 2013 presentation, detailing when/where/how external storage products and/or system software (i.e. GPFS) can be effectively used in a Hadoop storage environment. Many Hadoop situations absolutely required direct attached storage. However, there are many intelligent situations where shared external storage may make sense in a Hadoop environment. This presentation details how/why/where, and promotes taking an intelligent, Hadoop-aware approach to deciding between internal storage and external shared storage. Having full awareness of Hadoop considerations is essential to selecting either internal or external shared storage in Hadoop environment.
At the Virtual HPC User Forum Special Event, Dr. Gene Cooperman explains why Checpoint-Restarts are needed, the development of Distributed MultiThreaded CheckPointing (DMTC), and how persistent memory will help make DMTC practical to implement.
Unlocking a fully integrated Spark experience within your enterprise Hadoop environment that is manageable, secure and deployable anywhere.
Presented at the Spark Summit by Arun C Murthy (co-Founder, Hortonworks) on Monday, June 15, 2015.
This Hadoop HDFS Tutorial will unravel the complete Hadoop Distributed File System including HDFS Internals, HDFS Architecture, HDFS Commands & HDFS Components - Name Node & Secondary Node. Not only this, even Mapreduce & practical examples of HDFS Applications are showcased in the presentation. At the end, you'll have a strong knowledge regarding Hadoop HDFS Basics.
Session Agenda:
✓ Introduction to BIG Data & Hadoop
✓ HDFS Internals - Name Node & Secondary Node
✓ MapReduce Architecture & Components
✓ MapReduce Dataflows
----------
What is HDFS? - Introduction to HDFS
The Hadoop Distributed File System provides high-performance access to data across Hadoop clusters. It forms the crux of the entire Hadoop framework.
----------
What are HDFS Internals?
HDFS Internals are:
1. Name Node – This is the master node from where all data is accessed across various directores. When a data file has to be pulled out & manipulated, it is accessed via the name node.
2. Secondary Node – This is the slave node where all data is stored.
----------
What is MapReduce? - Introduction to MapReduce
MapReduce is a programming framework for distributed processing of large data-sets via commodity computing clusters. It is based on the principal of parallel data processing, wherein data is broken into smaller blocks rather than processed as a single block. This ensures a faster, secure & scalable solution. Mapreduce commands are based in Java.
----------
What are HDFS Applications?
1. Data Mining
2. Document Indexing
3. Business Intelligence
4. Predictive Modelling
5. Hypothesis Testing
----------
Skillspeed is a live e-learning company focusing on high-technology courses. We provide live instructor led training in BIG Data & Hadoop featuring Realtime Projects, 24/7 Lifetime Support & 100% Placement Assistance.
Email: sales@skillspeed.com
Website: https://www.skillspeed.com
MapReduce Tutorial | What is MapReduce | Hadoop MapReduce Tutorial | EdurekaEdureka!
This Edureka MapReduce Tutorial (MapReduce Tutorial blog: https://goo.gl/W0Rmtd) will help you understand the basic concepts of Hadoop's processing component - MapReduce. Below are the topics covered in this MapReduce Tutorial:
1) What is Hadoop MapReduce?
2) MapReduce In Nutshell
3) Advantages of MapReduce
4) Hadoop MapReduce Approach with an Example
5) Hadoop MapReduce/YARN Components
6) YARN With MapReduce
7) Yarn Application Workflow
8) Running a MapReduce Program
Check our complete Hadoop playlist here: https://goo.gl/ExJdZs
Rescue your Big Data from Downtime with HP Operations Bridge and Apache HadoopHortonworks
How can you simplify the management and monitoring of your Hadoop environment? Ensure IT can focus on the right business priorities supported by Hadoop? Take a look at this presentation and learn how you can simplify the management and monitoring of your Hadoop environment, and ensure IT can focus on the right business priorities supported by Hadoop.
Hadoop and Graph Data Management: Challenges and OpportunitiesDaniel Abadi
HadoopWorld 2011 Presentation by Daniel Abadi
As Hadoop rapidly becomes the universal standard for scalable data analysis and processing, it is increasingly important to understand its strengths and weaknesses for particular application scenarios in order to avoid inefficiency pitfalls. For example, Hadoop has great potential to perform scalable graph analysis if it is used correctly. Recent benchmarking has shown that simple implementations can be 1300 times less efficient than a more optimal Hadoop-centered implementation. In this talk, Daniel Abadi gives an overview of a recent research project at Yale University that investigates how to perform sub-graph pattern matching within a Hadoop-centered system that is three orders of magnitude faster than a more simple approach. This talk highlights how the cleaning, transforming, and parallel processing strengths of Hadoop are combined with storage optimized for graph data analysis. It then discusses further changes that are needed in the core Hadoop framework to take performance to the next level.
Covers different types of big data benchmarking, different suites, details into terasort, demo with TPCx-HS
Meetup Details of presentation:
http://www.meetup.com/lspe-in/events/203918952/
From HadoopDB to Hadapt: A Case Study of Transitioning a VLDB paper into Real...Daniel Abadi
VLDB 2013 Early Career Research Contribution Award Presentation
Abstract: Four years ago at VLDB 2009, a paper was published about a research prototype, called HadoopDB, that attempted to transform Hadoop --- a batch-oriented scalable system designed for processing unstructured data --- into a full-fledged parallel database system that can achieve real-time (interactive) query responses across both structured and unstructured data. In 2010 it was commercialized by Hadapt, a start-up that was formed to accelerate the engineering of the HadoopDB ideas, and to harden the codebase for deployment in real-world, mission-critical applications. In this talk I will give an overview of HadoopDB, and how it combines ideas from the Hadoop and database system communities. I will then describe how the project transitioned from a research prototype written by PhD students at Yale University into enterprise-ready software written by a team of experienced engineers. We will examine particular technical features that are required in enterprise Hadoop deployments, and technical challenges that we ran into while making HadoopDB robust enough to be deployed in the real world. The talk will conclude with an analysis of how starting a company impacts the tenure process, and some thoughts for graduate students and junior faculty considering a similar path.
How to Use Apache Zeppelin with HWX HDBHortonworks
Part five in a five-part series, this webcast will be a demonstration of the integration of Apache Zeppelin and Pivotal HDB. Apache Zeppelin is a web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more. This webinar will demonstrate the configuration of the psql interpreter and the basic operations of Apache Zeppelin when used in conjunction with Hortonworks HDB.
In 2017, more and more corporations are looking to reduce operational overheads in their enterprise data warehouse (EDW) installations. Hortonworks just launched Industry’s first turn key EDW Optimization solution together with our partners Syncsort and AtScale. Join Hortonworks’ CTO Scott Gnau to learn more about this exciting solution and its 3 use cases.
Forrester predicts, CIOs who are late to the Hadoop game will finally make the platform a priority in 2015. Hadoop has evolved as a must-to-know technology and has been a reason for better career, salary and job opportunities for many professionals.
Predictive Analytics and Machine Learning…with SAS and Apache HadoopHortonworks
In this interactive webinar, we'll walk through use cases on how you can use advanced analytics like SAS Visual Statistics and In-Memory Statistic with Hortonworks’ data platform (HDP) to reveal insights in your big data and redefine how your organization solves complex problems.
HPCフォーラム2015 B-1RandD 100 Award 受賞記念講演 常温水冷スパコンHP Apollo 8000開発エンジニアによる誕生秘話 N...日本ヒューレット・パッカード株式会社
日本HP主催イベント HPCフォーラム2015 トラックB(コミュニティトラック)
HP Tech Power Club 第3回スケールアウト分科会
データセンターの電力を少なくデザインするには?
常温水冷スパコン の誕生秘話
ヒューレット・パッカードカンパニー
最上級テクノロジスト
Nicolas Dobé, Ph.D
Unlocking a fully integrated Spark experience within your enterprise Hadoop environment that is manageable, secure and deployable anywhere.
Presented at the Spark Summit by Arun C Murthy (co-Founder, Hortonworks) on Monday, June 15, 2015.
This Hadoop HDFS Tutorial will unravel the complete Hadoop Distributed File System including HDFS Internals, HDFS Architecture, HDFS Commands & HDFS Components - Name Node & Secondary Node. Not only this, even Mapreduce & practical examples of HDFS Applications are showcased in the presentation. At the end, you'll have a strong knowledge regarding Hadoop HDFS Basics.
Session Agenda:
✓ Introduction to BIG Data & Hadoop
✓ HDFS Internals - Name Node & Secondary Node
✓ MapReduce Architecture & Components
✓ MapReduce Dataflows
----------
What is HDFS? - Introduction to HDFS
The Hadoop Distributed File System provides high-performance access to data across Hadoop clusters. It forms the crux of the entire Hadoop framework.
----------
What are HDFS Internals?
HDFS Internals are:
1. Name Node – This is the master node from where all data is accessed across various directores. When a data file has to be pulled out & manipulated, it is accessed via the name node.
2. Secondary Node – This is the slave node where all data is stored.
----------
What is MapReduce? - Introduction to MapReduce
MapReduce is a programming framework for distributed processing of large data-sets via commodity computing clusters. It is based on the principal of parallel data processing, wherein data is broken into smaller blocks rather than processed as a single block. This ensures a faster, secure & scalable solution. Mapreduce commands are based in Java.
----------
What are HDFS Applications?
1. Data Mining
2. Document Indexing
3. Business Intelligence
4. Predictive Modelling
5. Hypothesis Testing
----------
Skillspeed is a live e-learning company focusing on high-technology courses. We provide live instructor led training in BIG Data & Hadoop featuring Realtime Projects, 24/7 Lifetime Support & 100% Placement Assistance.
Email: sales@skillspeed.com
Website: https://www.skillspeed.com
MapReduce Tutorial | What is MapReduce | Hadoop MapReduce Tutorial | EdurekaEdureka!
This Edureka MapReduce Tutorial (MapReduce Tutorial blog: https://goo.gl/W0Rmtd) will help you understand the basic concepts of Hadoop's processing component - MapReduce. Below are the topics covered in this MapReduce Tutorial:
1) What is Hadoop MapReduce?
2) MapReduce In Nutshell
3) Advantages of MapReduce
4) Hadoop MapReduce Approach with an Example
5) Hadoop MapReduce/YARN Components
6) YARN With MapReduce
7) Yarn Application Workflow
8) Running a MapReduce Program
Check our complete Hadoop playlist here: https://goo.gl/ExJdZs
Rescue your Big Data from Downtime with HP Operations Bridge and Apache HadoopHortonworks
How can you simplify the management and monitoring of your Hadoop environment? Ensure IT can focus on the right business priorities supported by Hadoop? Take a look at this presentation and learn how you can simplify the management and monitoring of your Hadoop environment, and ensure IT can focus on the right business priorities supported by Hadoop.
Hadoop and Graph Data Management: Challenges and OpportunitiesDaniel Abadi
HadoopWorld 2011 Presentation by Daniel Abadi
As Hadoop rapidly becomes the universal standard for scalable data analysis and processing, it is increasingly important to understand its strengths and weaknesses for particular application scenarios in order to avoid inefficiency pitfalls. For example, Hadoop has great potential to perform scalable graph analysis if it is used correctly. Recent benchmarking has shown that simple implementations can be 1300 times less efficient than a more optimal Hadoop-centered implementation. In this talk, Daniel Abadi gives an overview of a recent research project at Yale University that investigates how to perform sub-graph pattern matching within a Hadoop-centered system that is three orders of magnitude faster than a more simple approach. This talk highlights how the cleaning, transforming, and parallel processing strengths of Hadoop are combined with storage optimized for graph data analysis. It then discusses further changes that are needed in the core Hadoop framework to take performance to the next level.
Covers different types of big data benchmarking, different suites, details into terasort, demo with TPCx-HS
Meetup Details of presentation:
http://www.meetup.com/lspe-in/events/203918952/
From HadoopDB to Hadapt: A Case Study of Transitioning a VLDB paper into Real...Daniel Abadi
VLDB 2013 Early Career Research Contribution Award Presentation
Abstract: Four years ago at VLDB 2009, a paper was published about a research prototype, called HadoopDB, that attempted to transform Hadoop --- a batch-oriented scalable system designed for processing unstructured data --- into a full-fledged parallel database system that can achieve real-time (interactive) query responses across both structured and unstructured data. In 2010 it was commercialized by Hadapt, a start-up that was formed to accelerate the engineering of the HadoopDB ideas, and to harden the codebase for deployment in real-world, mission-critical applications. In this talk I will give an overview of HadoopDB, and how it combines ideas from the Hadoop and database system communities. I will then describe how the project transitioned from a research prototype written by PhD students at Yale University into enterprise-ready software written by a team of experienced engineers. We will examine particular technical features that are required in enterprise Hadoop deployments, and technical challenges that we ran into while making HadoopDB robust enough to be deployed in the real world. The talk will conclude with an analysis of how starting a company impacts the tenure process, and some thoughts for graduate students and junior faculty considering a similar path.
How to Use Apache Zeppelin with HWX HDBHortonworks
Part five in a five-part series, this webcast will be a demonstration of the integration of Apache Zeppelin and Pivotal HDB. Apache Zeppelin is a web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more. This webinar will demonstrate the configuration of the psql interpreter and the basic operations of Apache Zeppelin when used in conjunction with Hortonworks HDB.
In 2017, more and more corporations are looking to reduce operational overheads in their enterprise data warehouse (EDW) installations. Hortonworks just launched Industry’s first turn key EDW Optimization solution together with our partners Syncsort and AtScale. Join Hortonworks’ CTO Scott Gnau to learn more about this exciting solution and its 3 use cases.
Forrester predicts, CIOs who are late to the Hadoop game will finally make the platform a priority in 2015. Hadoop has evolved as a must-to-know technology and has been a reason for better career, salary and job opportunities for many professionals.
Predictive Analytics and Machine Learning…with SAS and Apache HadoopHortonworks
In this interactive webinar, we'll walk through use cases on how you can use advanced analytics like SAS Visual Statistics and In-Memory Statistic with Hortonworks’ data platform (HDP) to reveal insights in your big data and redefine how your organization solves complex problems.
HPCフォーラム2015 B-1RandD 100 Award 受賞記念講演 常温水冷スパコンHP Apollo 8000開発エンジニアによる誕生秘話 N...日本ヒューレット・パッカード株式会社
日本HP主催イベント HPCフォーラム2015 トラックB(コミュニティトラック)
HP Tech Power Club 第3回スケールアウト分科会
データセンターの電力を少なくデザインするには?
常温水冷スパコン の誕生秘話
ヒューレット・パッカードカンパニー
最上級テクノロジスト
Nicolas Dobé, Ph.D
How HPC Transforms the Corporate Information Technology Ecosysteminside-BigData.com
In this deck from the 2015 PBS Works User Group, Thomas Leung from the GE Global Research Center presents: HPC Across the Enterprise: How HPC Transforms the Corporate Information Technology Ecosystem.
"The commercial world uses significant HPC resources for simulation and product design. An increasing number of HPC systems are deployed in the commercial space and their scale is getting larger and larger. These advanced systems push limits in every aspect of Enterprise IT. Accommodating such systems within the enterprise is a challenge, and there have been many recent changes to enterprise IT infrastructures and architectures resulting from the need to support HPC. Although Commercial HPC is part of the Supercomputing family, Commercial HPC has unique focus areas and challenges. Cloud, Data Lake, Industrial Internet, Internet of Things and Big Data have created a huge impact on HPC systems. Each of these initiatives offers new opportunities to both HPC itself and to the enterprise. HPC systems must change themselves to accept and accommodate these changes. This presentation covers how HPC transforms science in a corporate information technology ecosystem. It also explains the differences between Research HPC and Commercial HPC in terms of architecture, usage, resource planning and challenges."
Learn more: http://www.pbsworks.com/pbsug/2015/agenda.aspx
Watch the video presentation: https://youtu.be/bpP-HSLvzPg
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
In this video from Moabcon 2013, Dick Bland and Jérôme Labat from HP present: The New Style of IT: HP Update for Moabcon 2013.
"Cloud, Mobility, Security, and Big Data are transforming what the business expects from IT resulting in a “New Style of IT.” The result of alternative thinking from a proven industry leader, HP Moonshot is the world’s first software defined server that will accelerate innovation while delivering breakthrough efficiency and scale."
While the first spin of Moonshot is not targeted at HPC, Bland said that HP will be able to spin up new modules for the platform that could include FPGAs and ARM-based nodes more suited to high performance computing.
Learn more at: http://www.adaptivecomputing.com/company/news-and-events/events/moabcon-2013/moabcon-2013-full-agenda/
You can watch the video of this talk at this URL: http://inside-cloud.com/2013/04/video-the-new-style-of-it-hp-moonshot-update-for-moabcon-2013/
Integrated asset model can provide a single source of the truth across the full stream for how molecules and operating conditions behave at the unit- and asset-wide level;
Thereby providing actionable insights into production activities that can drive convergence in decision-making and action across organizational silos.
Linda Knippers – Distinguished Technologist at HP
Keynote title: “Fueling HP Moonshot”
Abstract: HP’s participation in Linux and open source communities and organizations and how Linaro/ LEG is enabling HP Moonshot.
Linda Knippers' Bio: Linda works in technology and strategy for Linux and Open Source in HP’s Enterprise Group, Server division.
---------------------------------------------------
★ Resources ★
Zerista: http://lcu14.zerista.com/event/member/137745
Google Event: https://plus.google.com/u/0/events/c0tpq84v6f65tua2l2e0cqe9j5s
Video: https://www.youtube.com/watch?v=69OqKQ_NcTQ&list=UUIVqQKxCyQLJS6xvSmfndLA
Etherpad: http://pad.linaro.org/p/lcu14-300b
---------------------------------------------------
★ Event Details ★
Linaro Connect USA - #LCU14
September 15-19th, 2014
Hyatt Regency San Francisco Airport
---------------------------------------------------
http://www.linaro.org
http://connect.linaro.org
Keynote Address given by Paul Strassman, former Director of Defense Information and current Distinguished Professor of Information Science at George Mason University, at Transformation and Innovation 2007.
I hosted a webcast with Sr. VP and GM of HP Storage David Scott. David and I talked about flash-optimized storage and the software defined data center. You can find the audio for the webcast at http://hpstorage.me/ASTB-podcasts - they are number 146 and 147.
A modern, flexible approach to Hadoop implementation incorporating innovation...DataWorks Summit
A modern, flexible approach to Hadoop implementation incorporating innovations from HP Haven
Jeff Veis
Vice President
HP Software Big Data
Gilles Noisette
Master Solution Architect
HP EMEA Big Data CoE
Presentation given at IMCW 2013 in Limerick. Discussing how the combination of cloud, social, mobile and big data will transform our world moving forward. What can you do to be part of this new revolution
Presentations on Data Center Sustainability from:
• Dale Sartor, Staff Engineer, Building and Industrial Applications, Lawrence Berkeley National Laboratory
• Orlando Figueredo, Vice President, Consulting and Intelligence, Hewlett Packard Enterprise
• Barbara Humpton, President and CEO, Siemens Government Technologies, Inc.
HP 3Par StoreServ Storage: HP All Flash Array SSDUnitiv
Solid state drives are a game changer in the storage market. At this point, the performance benefits are common knowledge. But what might not be common knowledge is that SSDs have surpassed high speed spinning disk in capacity density. In the past 5 years, SSDs have increased in capacity by a magnitude of 38x while high speed spinning disks have only doubled
And HP has been helping to drive this transition by working very closely with our SSD suppliers. For example, we are the only major storage vendor to offer a 1.92 TB drive. Our patented Adaptive Sparing technology, which is unique to HP, let’s us work with the SSD vendors to take stock 1.6 TB drives and extend them to 1.92 based on the technology. That’s an increase in usable capacity per drive of up to 20%.
In June we announced this drive for the All-flash 7450 system and we are now extending this across the entire 3PAR Portfolio.
For customers that are interested in deploying Flash in smaller increments, we are also introducing a 480 cMLC Drive across the entire portfolio.
http://www.unitiv.com/hp-all-flash-array/
Chia sẻ kinh nghiệm học cờ cùng con - Nguyễn Vũ Kỳ Anh U8
Tham khảo:
Học cờ cùng con U6 https://www.slideshare.net/vuhung16plus/hoc-co-cung-con
Học cờ cùng con U7 https://www.slideshare.net/vuhung16plus/2018-hoc-co-cung-co-nguyen-vu-ky-anh-u7
2018 Học cờ cùng con - Nguyễn Vũ Kỳ Anh [U7]Vu Hung Nguyen
Chia sẻ kinh nghiệm học/dạy cờ với Nguyễn Vũ Kỳ Anh trong khoảng thời gian 1 năm U7
Học cờ cùng con U6 https://www.slideshare.net/vuhung16plus/hoc-co-cung-con
Học cờ cùng con U7 https://www.slideshare.net/vuhung16plus/2018-hoc-co-cung-co-nguyen-vu-ky-anh-u7
Học cờ cùng con U8 https://www.slideshare.net/vuhung16plus/hoc-co-cung-con-nguyen-vu-ky-anh-u8/
FPT Univ. Talkshow IT khong chi la lap trinhVu Hung Nguyen
FPT Univ. Talkshow: IT không chỉ là lập trình.
Nội dung:
Làm IT là làm cái gì?
Làm IT thì KHÔNG là cái gì?
Lập trình & kỹ năng cần thiết
Những nẻo đường IT (khác) (not coder)
Nghề gì lương cao? Cao bao nhiêu?
Giỏi code chưa chắc đã được gửi xe
(Kỹ năng) Cứng và mềm: Cầm cái nào?
Để coder nổi bật giữa đám đông
Fullstack làm (được) gì?
Kế hoạch cuộc đời
Basic & Advanced Scrum Framework / Scrum cơ bản và nâng cao:
Điểm nhấn:
- 100+ slides
- Nhiều nội dung từ cơ bản đến cao cấp
- Nhiều cách học (tự học cá nhân, theo nhóm)
- In-house training available (liên lạc tôi: Vũ Hưng...)
Nội dung chính:
- Giới thiệu & lịch sử Scrum
- Scrum cơ bản
- Scrum nâng cao
- Những câu hỏi thường gặp
- Các tình huống thực tế
- Bộ công cụ Agile/Scrum
- Trao đổi/thảo luận
File gốc: https://docs.google.com/presentation/d/1bnZTSitzNn9TTY1nJbYG2fA_Z3BriUoAvHqZorOABqg/edit#slide=id.g1ad7d55466_0_96
TALKSHOW – KHỞI ĐẦU TỪ SAU NHỮNG DÒNG CODE
Với mục tiêu tạo thêm nhiều cơ hội cho các bạn sinh viên ngành CNTT có cơ hội cọ xát kiến thức đã học với thực tế công việc qua việc tương tác cùng các chuyên gia có nhiều năm kinh nghiệm làm việc trong lĩnh vực CNTT,
⭐ Anh Nguyễn Vũ Hưng - Chuyên viên hướng nghiệp, Mentor tại FUNIX, thành viên hội đồng quản trị IT Experts Club và Agile Viet Nam.
⭐ Anh Bùi Xuân Cảnh - Sinh viên K1 Đại học FPT, hiện đang là Quản trị dự án tại FPT Software - FPT Top 100 Excellent Person Of The Year
Cùng tới tham dự Talkshow, để được:
⭐ Có cơ hội trao đổi trực tiếp và giải đáp các thắc mắc, trăn trở về định hướng nghề nghiệp tương lai,
⭐ Được tìm hiểu và thực hành các kiến thức, kỹ năng cần thiết của một kỹ sư CNTT,
⭐ VỚI CÁC SINH VIÊN SẮP RA TRƯỜNG các bạn sẽ được thỏa sức trong những chia sẻ kinh nghiệm, trải nghiệm phỏng vấn, cách đàm phán lương, trả lời phỏng vấn và câu chuyện khởi đầu từ chính trải nghiệm của các diễn giả.
Thời gian: từ 19:00 thứ Năm, ngày 02/03/2017
Địa điểm: Hội trường tầng 1, Tòa nhà Beta - Đại học FPT.
Đối tượng tham gia: Cán bộ, Giảng viên, Sinh viên ngành CNTT, trường Đại học FPT - cơ sở Hòa Lạc
Event link:
https://www.facebook.com/events/1851290055094563/
Mục đích:
Tài liệu này hướng dẫn các bước, cách chuẩn bị, techniques/tips cho một bài phát biểu. Áp dụng cho ngành IT (là chính)
Đối tượng:
Diễn giả
# Các buổi chia sẻ về IT/Công nghệ
# Đặc biệt là những diễn giả lần đầu phát biểu
Thuyết trình
Ban tổ chức sự kiện
MC sự kiện
Chia sẻ kinh nghiệm học/dạy cờ cùng con Nguyễn Vũ Kỳ Anh (U6)
Học cờ cùng con U6 https://www.slideshare.net/vuhung16plus/hoc-co-cung-con
Học cờ cùng con U7 https://www.slideshare.net/vuhung16plus/2018-hoc-co-cung-co-nguyen-vu-ky-anh-u7
Học cờ cùng con U8 https://www.slideshare.net/vuhung16plus/hoc-co-cung-con-nguyen-vu-ky-anh-u8/
Anti patterns in it project management. Speech at Agile Vietnam 2016 Conference.
20161016 Agile Vietnam Conference 2016
---
http://www.agilevietnam.org/conf/2016/index.html
https://www.facebook.com/events/892107294257261/
#agilevn16, #agilevietnam2016, #hanoi, #altplus
[AGILE VIETNAM CONFERENCE 2016] - A regional conference on Agile practices, software craftsmanship and organization improvement.
5 years in a row, Agile Vietnam has achieved numerous success and has impacted positively on the community. With that spirit, Agile Vietnam has been very proud to hold Agile Vietnam Conference 2016.
Agile Vietnam Conference 2016 aims to be the best and the biggest event held by Agile Vietnam Community with theme of "LEAPFROG" - with full of exciting activities including keynote speeches, workshops, contests, games, business matching, and networking.
Why you should come to Agile Vietnam 2016 Conference?
➡ Networking with top experts of the world
➡ Improve agile process and project outcomes
➡ Inspire your mind
➡ Exclusive opportunity for learning
➡ Attend a world-class conference
►►►DATE & VENUE: (HCMC - DANANG CITY - HANOI CAPITAL)
● 07:30 - 17:00, 14th October 2016, Hoa Sen University, Nguyen Van Trang, District 1, HCMC.
● 07:30 - 12:00, 15th October 2016, Bamboo Green Hotel 177 Tran Phu, Hai Chau, Danang.
● 07:00 - 17:00, 16th October 2016, Alt Plus Vietnam Company Limited, 31F Keangnam Ha Noi Landmark Tower 72, Lot E6 Pham Hung, Nam Tu Liem, Ha Noi.
►►►TICKET INFORMATION:
● Eventbrite: http://goo.gl/I8GFVC
● Ticket box:
- HCM: https://goo.gl/6fPbWD
- Ha Noi: https://goo.gl/3wk4Yv
- Da Nang: https://goo.gl/Gc2mtF
►►►More information: http://goo.gl/4K8EdQ
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.