The National Center for Biotechnology Information (NCBI) at the National Institutes of Health (NIH) requires high-performance storage to support genome research for its public databases and projects like the 1000 Genomes Project. NCBI's existing storage could not scale to meet the demands of projects generating over 1.5 petabytes of genetic data. NCBI implemented a Panasas storage system connected to a 1800-core Dell cluster, which improved application performance by 5 times, enabled faster database updates, and provided scalable storage for NCBI's growing archives. The Panasas solution supports NCBI's mission of advancing biomedical discovery through public databases and genome research.
Whitepaper : CHI: Hadoop's Rise in Life Sciences EMC
Genomics large, semi-structured, file-based data is ideally suited for a Hadoop Distributed File System. The EMC Isilon OneFS file system features connectivity to the Hadoop Distributed File System (HDFS) that makes the Hadoop storage "oscale-out" and truly distributed. An example from the "CrossBow" project is explored.
White Paper: Life Sciences at RENCI, Big Data IT to Manage, Decipher and Info...EMC
This white paper explains how the Renaissance Computing Institute (RENCI) of the University of North Carolina uses EMC Isilon scale-out NAS storage, Intel processor and system technology, and iRODS-based data management to tackle Big Data processing, Hadoop-based analytics, security and privacy challenges in research and clinical genomics.
UCSC's Biomolecular Department Eliminates I/O Bottleneck with PanasasPanasas
Slow I/O and downtime impacted the run times of the University of California Santa Cruz's Genome Browser search tool used by scientists in their work to solve questions of the postgenomic era. They were searching for a storage solution that delivered high performance random I/O to an exceptionally large number of cluster nodes and one that would allow them to focus solely on their tests instead of the systems running them.
Knowledge Organization System (KOS) for biodiversity information resources, G...Dag Endresen
Slides from a presentation on the Knowledge Organization System (KOS) work program for GBIF. KOS developments for biodiversity information resources and input to the emerging Vocabulary Management Task Group (VoMaG).
Links
GBIF KOS prototype tools, http://kos.gbif.org/
Tool: Semantic Wiki prototype, http://terms.gbif.org/wiki/
Tool: ISOcat prototype demo, http://kos.gbif.org/isocat/
GBIF concept vocabulary term browser, http://kos.gbif.org/termbrowser/
GBIF Resources Repository, http://rs.gbif.org/terms/
GBIF Vocabulary Server, http://vocabularies.gbif.org/
GBIF Resources Browser, http://tools.gbif.org/resource-browser/
Whitepaper : CHI: Hadoop's Rise in Life Sciences EMC
Genomics large, semi-structured, file-based data is ideally suited for a Hadoop Distributed File System. The EMC Isilon OneFS file system features connectivity to the Hadoop Distributed File System (HDFS) that makes the Hadoop storage "oscale-out" and truly distributed. An example from the "CrossBow" project is explored.
White Paper: Life Sciences at RENCI, Big Data IT to Manage, Decipher and Info...EMC
This white paper explains how the Renaissance Computing Institute (RENCI) of the University of North Carolina uses EMC Isilon scale-out NAS storage, Intel processor and system technology, and iRODS-based data management to tackle Big Data processing, Hadoop-based analytics, security and privacy challenges in research and clinical genomics.
UCSC's Biomolecular Department Eliminates I/O Bottleneck with PanasasPanasas
Slow I/O and downtime impacted the run times of the University of California Santa Cruz's Genome Browser search tool used by scientists in their work to solve questions of the postgenomic era. They were searching for a storage solution that delivered high performance random I/O to an exceptionally large number of cluster nodes and one that would allow them to focus solely on their tests instead of the systems running them.
Knowledge Organization System (KOS) for biodiversity information resources, G...Dag Endresen
Slides from a presentation on the Knowledge Organization System (KOS) work program for GBIF. KOS developments for biodiversity information resources and input to the emerging Vocabulary Management Task Group (VoMaG).
Links
GBIF KOS prototype tools, http://kos.gbif.org/
Tool: Semantic Wiki prototype, http://terms.gbif.org/wiki/
Tool: ISOcat prototype demo, http://kos.gbif.org/isocat/
GBIF concept vocabulary term browser, http://kos.gbif.org/termbrowser/
GBIF Resources Repository, http://rs.gbif.org/terms/
GBIF Vocabulary Server, http://vocabularies.gbif.org/
GBIF Resources Browser, http://tools.gbif.org/resource-browser/
Genomics Center Compares 100s of Computations Simultaneously with PanasasPanasas
The Center for Integrative Genomics brings together researchers from traditionally separated fields of study to analyze and compare the genome sequences of a broad spectrum of organisms in order to determine the mechanisms responsible for evolutionary diversity among animals, plants and microbes. The university was facing a challenge to quickly and easily conduct comparative analyses of hundreds of computations required to accomplish their mission to research and understand gene regulation. Here is how the integrated software/hardware solution which includes the Panasas Operating Environment and the PanFS™ parallel filesystem with the Panasas DirectFLOW® protocol helped the University to achieve exceptional performance.
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...Bonnie Hurwitz
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to microbes. Overview of work underway to add applications and computational analysis pipelines to iPlant for metagenomics and microbial ecology.
This presentation focuses on the networking requirements using open source to treat diseases through cell-based analysis at the molecular level. Transporting this knowledge across devices and centers requires a whole new structure and networking. Terabits per second with high-availability and guaranteed delivery is required to meet the needs. Shared knowledge is the critical for real-time analysis. This will discuss data flows, open networking, and databases that are all open source and have been optimized for this problem.
Established in 2007, QFAB focuses on delivering robust, high quality and relevant bioinformatics services for life science researchers to analyse and manage large-scale datasets.
Our support ranges from experimental design, data capture and mining through to NGS, proteomic and metabolomic analyses. We are also expert in cross-domain integration with clinical data.
QFAB can work on specific projects, provide time against an ongoing need or become embedded in your organisation. Flexible, rapid and researcher oriented, QFAB has built a reputation for supporting the production of high quality outcomes which deliver those high impact publications or patents faster.
www.qfab.org
Life science research organizations are
re-evaluating their storage strategies in the
face of rapidly growing volumes of critically
important data. The increased use of
advanced gene sequencing and medical
imaging applications are taxing legacy
storage infrastructures. Life sciences
applications are driving the need for fast,
extremely scalable, easy-to-manage, and
affordable high-performance storage
systems that handle intense technical
workloads while accelerating time-to-results
The Andrej Sali Lab Processes Millions of Small Files with PanasasPanasas
The University of California, San Francisco (UCSF) needed a computing solution that could process millions of small files as quickly as possible for researchers identifying the structural similarities of protein models. They needed to eliminate poor storage system performance and significantly decrease administrator management time and within a limited budget. Here is how the fully integrated software/hardware solution including the Panasas Operating Environment and the PanFS parallel file system with the Panasas DirectFLOW protocol helped UCSF to overcome the challenges.
How novel compute technology transforms life science researchDenis C. Bauer
Unprecedented data volumes and pressure on turnaround time driven by commercial applications require bioinformatics solutions to evolve to meed these new demands. New compute paradigms and cloud-based IT solutions enable this transition. Here I present two solution capable of meeting these demands for genomic variant analysis, VariantSpark, as well as genome engineering applications, GT-Scan2.
VariantSpark classifies 3000 individuals with 80 Million genomic variants each in under 30 minutes. This Hadoop/Spark solution for machine learning application on genomic data is hence capable to scale up to population size cohorts.
GT-Scan2, identifies CRISPR target sites by minimizing off-target effects and maximizing on-target efficiency. This optimization is powered by AWS Lambda functions, which offer an “always-on” web service that can instantaneously recruit enough compute resources keep runtime stable even for queries with several thousand of potential target sites.
HPC and Precision Medicine: A New Framework for Alzheimer's and Parkinson'sinside-BigData.com
In this deck from the HPC User Forum in Tucson, Joe Lombardo from UNLV presents: HPC and Precision Medicine - A New Framework for Alzheimer's and Parkinson's.
"The University of Nevada, Las Vegas and the Cleveland Clinic Lou Ruvo Center for Brain Health have been awarded an $11 million federal grant from the National Institutes of Health and National Institute of General Medical Sciences to advance the understanding of Alzheimer's and Parkinson's diseases. In this session, we will present how UNLV's National Supercomputing Institute plays a critical role in this research by fusing brain imaging, neuropsychological and behavioral studies along with the diagnostic exome sequencing models to increase our knowledge of dementia-related and age-associated degenerative disorders."
Watch the video: https://wp.me/p3RLHQ-iws
Learn more: https://www.unlv.edu/news/release/unlv-receives-nih-grant-alzheimers-disease-research
and
http://hpcuserforum.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Presentation given by Appistry's Vice President of Product Strategy, Sultan Meghi at the World Genome Data Analysis Summit. Meghi presented about the big data challenges facing labs as they strive to manage the flow of genetic data from sequencer to the clinic.
VariantSpark: applying Spark-based machine learning methods to genomic inform...Denis C. Bauer
Genomic information is increasingly used in medical practice giving rise to the need for efficient analysis methodology able to cope with thousands of individuals and millions of variants. Here we introduce VariantSpark, which utilizes Hadoop/Spark along with its machine learning library, MLlib, providing the means of parallelisation for population-scale bioinformatics tasks. VariantSpark is the interface to the standard variant format (VCF), offers seamless genome-wide sampling of variants and provides a pipeline for visualising results.
To demonstrate the capabilities of VariantSpark, we clustered more than 3,000 individuals with 80 Million variants each to determine the population structure in the dataset. VariantSpark is 80% faster than the Spark-based genome clustering approach, ADAM, the comparable implementation using Hadoop/Mahout, as well as Admixture, a commonly used tool for determining individual ancestries. It is over 90% faster than traditional implementations using R and Python. These benefits of speed, resource consumption and scalability enables VariantSpark to open up the usage of advanced, efficient machine learning algorithms to genomic data.
The package is written in Scala and available at https://github.com/BauerLab/VariantSpark.
Is Your Storage Ready for Commercial HPC? - Three Steps to TakePanasas
Learn why:
1. HPC workloads are on the rise
2. Enterprise storage can't meet HPC demands
3. Traditional HPC storage is a poor fit
4. 3 Steps to design Enterprise-Class HPC
Genomics Center Compares 100s of Computations Simultaneously with PanasasPanasas
The Center for Integrative Genomics brings together researchers from traditionally separated fields of study to analyze and compare the genome sequences of a broad spectrum of organisms in order to determine the mechanisms responsible for evolutionary diversity among animals, plants and microbes. The university was facing a challenge to quickly and easily conduct comparative analyses of hundreds of computations required to accomplish their mission to research and understand gene regulation. Here is how the integrated software/hardware solution which includes the Panasas Operating Environment and the PanFS™ parallel filesystem with the Panasas DirectFLOW® protocol helped the University to achieve exceptional performance.
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...Bonnie Hurwitz
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to microbes. Overview of work underway to add applications and computational analysis pipelines to iPlant for metagenomics and microbial ecology.
This presentation focuses on the networking requirements using open source to treat diseases through cell-based analysis at the molecular level. Transporting this knowledge across devices and centers requires a whole new structure and networking. Terabits per second with high-availability and guaranteed delivery is required to meet the needs. Shared knowledge is the critical for real-time analysis. This will discuss data flows, open networking, and databases that are all open source and have been optimized for this problem.
Established in 2007, QFAB focuses on delivering robust, high quality and relevant bioinformatics services for life science researchers to analyse and manage large-scale datasets.
Our support ranges from experimental design, data capture and mining through to NGS, proteomic and metabolomic analyses. We are also expert in cross-domain integration with clinical data.
QFAB can work on specific projects, provide time against an ongoing need or become embedded in your organisation. Flexible, rapid and researcher oriented, QFAB has built a reputation for supporting the production of high quality outcomes which deliver those high impact publications or patents faster.
www.qfab.org
Life science research organizations are
re-evaluating their storage strategies in the
face of rapidly growing volumes of critically
important data. The increased use of
advanced gene sequencing and medical
imaging applications are taxing legacy
storage infrastructures. Life sciences
applications are driving the need for fast,
extremely scalable, easy-to-manage, and
affordable high-performance storage
systems that handle intense technical
workloads while accelerating time-to-results
The Andrej Sali Lab Processes Millions of Small Files with PanasasPanasas
The University of California, San Francisco (UCSF) needed a computing solution that could process millions of small files as quickly as possible for researchers identifying the structural similarities of protein models. They needed to eliminate poor storage system performance and significantly decrease administrator management time and within a limited budget. Here is how the fully integrated software/hardware solution including the Panasas Operating Environment and the PanFS parallel file system with the Panasas DirectFLOW protocol helped UCSF to overcome the challenges.
How novel compute technology transforms life science researchDenis C. Bauer
Unprecedented data volumes and pressure on turnaround time driven by commercial applications require bioinformatics solutions to evolve to meed these new demands. New compute paradigms and cloud-based IT solutions enable this transition. Here I present two solution capable of meeting these demands for genomic variant analysis, VariantSpark, as well as genome engineering applications, GT-Scan2.
VariantSpark classifies 3000 individuals with 80 Million genomic variants each in under 30 minutes. This Hadoop/Spark solution for machine learning application on genomic data is hence capable to scale up to population size cohorts.
GT-Scan2, identifies CRISPR target sites by minimizing off-target effects and maximizing on-target efficiency. This optimization is powered by AWS Lambda functions, which offer an “always-on” web service that can instantaneously recruit enough compute resources keep runtime stable even for queries with several thousand of potential target sites.
HPC and Precision Medicine: A New Framework for Alzheimer's and Parkinson'sinside-BigData.com
In this deck from the HPC User Forum in Tucson, Joe Lombardo from UNLV presents: HPC and Precision Medicine - A New Framework for Alzheimer's and Parkinson's.
"The University of Nevada, Las Vegas and the Cleveland Clinic Lou Ruvo Center for Brain Health have been awarded an $11 million federal grant from the National Institutes of Health and National Institute of General Medical Sciences to advance the understanding of Alzheimer's and Parkinson's diseases. In this session, we will present how UNLV's National Supercomputing Institute plays a critical role in this research by fusing brain imaging, neuropsychological and behavioral studies along with the diagnostic exome sequencing models to increase our knowledge of dementia-related and age-associated degenerative disorders."
Watch the video: https://wp.me/p3RLHQ-iws
Learn more: https://www.unlv.edu/news/release/unlv-receives-nih-grant-alzheimers-disease-research
and
http://hpcuserforum.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Presentation given by Appistry's Vice President of Product Strategy, Sultan Meghi at the World Genome Data Analysis Summit. Meghi presented about the big data challenges facing labs as they strive to manage the flow of genetic data from sequencer to the clinic.
VariantSpark: applying Spark-based machine learning methods to genomic inform...Denis C. Bauer
Genomic information is increasingly used in medical practice giving rise to the need for efficient analysis methodology able to cope with thousands of individuals and millions of variants. Here we introduce VariantSpark, which utilizes Hadoop/Spark along with its machine learning library, MLlib, providing the means of parallelisation for population-scale bioinformatics tasks. VariantSpark is the interface to the standard variant format (VCF), offers seamless genome-wide sampling of variants and provides a pipeline for visualising results.
To demonstrate the capabilities of VariantSpark, we clustered more than 3,000 individuals with 80 Million variants each to determine the population structure in the dataset. VariantSpark is 80% faster than the Spark-based genome clustering approach, ADAM, the comparable implementation using Hadoop/Mahout, as well as Admixture, a commonly used tool for determining individual ancestries. It is over 90% faster than traditional implementations using R and Python. These benefits of speed, resource consumption and scalability enables VariantSpark to open up the usage of advanced, efficient machine learning algorithms to genomic data.
The package is written in Scala and available at https://github.com/BauerLab/VariantSpark.
Similar to National Institutes of Health Maximize Computing Resources with Panasas (20)
Is Your Storage Ready for Commercial HPC? - Three Steps to TakePanasas
Learn why:
1. HPC workloads are on the rise
2. Enterprise storage can't meet HPC demands
3. Traditional HPC storage is a poor fit
4. 3 Steps to design Enterprise-Class HPC
The combination of scalable ANSYS design and simulation software and HPC clusters with Panasas parallel storage has demonstrated new and significant productivity advantages for workflows in computer aided engineering (CAE) applications. The combination provides
dramatic cost-performance improvements and speeds time-to-results for engineering simulation solutions on commodity HPC clusters
Panasas ® California Institute of Technology Success StoryPanasas
The Center for Advanced Computing Research (CACR) at the California Institute of Technology (Caltech) operates large-scale computing facilities for numerous campus
research groups who have big data design and discovery requirements. CACR has a full-time, 25-person staff with expertise in data-intensive scientific discovery, physicsbased simulation, scientific software engineering, visualization, and novel computer
architectures. It provides technical assistance such as porting code, designing and specifying resources, and advanced IT integration.
Panasas ® University of Cologne Success StoryPanasas
In 2004, the Center for Applied Informatics at the
University of Cologne in Germany, sought to bring
high-performance computing (HPC) in the form of
Linux cluster computing to one of the oldest and most
prestigious institutions of higher education. Over
the years as the demand on their HPC resources
continued to grow, their existing storage systems could
not keep pace. This case study details the challenges
faced by the Center at the University of Cologne and
how Panasas storage successfully met the Center’s
requirements for a scalable, ultra high-performance
storage infrastructure.
CD-adapco is the world’s largest independent CFD-focused provider of engineering simulation software, support, and services. The company’s STAR-CCM+ provides comprehensive simulation capability for solving problems involving flow of fluids and solids, heat transfer, and stress within a single integrated package. Obtaining results quickly requires extreme processing power matched to a big data storage solution that eliminates I/O bottlenecks.
Deluxe Australia is a leading provider of services and technologies to the worldwide entertainment industry including top Hollywood studios. For nearly a century, Deluxe has provided content owners and creators with the tools and talent they need to bring the most compelling and exciting stories to life. Deluxe specializes in production,
post-production, distribution, and asset management.
Oxford University’s Advanced Research Computing (ARC) facility (formerly known as the Oxford SuperComputing Centre) is a central resource available to researchers from
any discipline that need access to High Performance Computing (HPC) capabilities. By offering the ability to store large data sets accessed by high performance applications running on large compute clusters, researchers can tackle larger, more complex
questions with ease. ARC relies on its Panasas ActiveStor hybrid scale-out NAS solution to provide fast, reliable, and easy-to-administer storage around the clock to support
researchers’ diverse work flows.
TerraSpark Geosciences designs software tools for energy exploration and production. Its flagship product, Insight Earth, enables visualization-guided 3D seismic volume interpretation of structure and stratigraphy, and integrated directional well-path planning
The Institute for Digital Research and Education (IDRE) at the University of California at Los Angeles (UCLA) provides a high performance computing (HPC) private cloud to empower university scholars with the computational resources they need for core
design and discovery. Through the collaborative efforts of its experienced team of researchers, IDRE helps make UCLA a world leader in high-performance computing,
visualization research, and education.
Panasas ® The Defence Academy of the United Kingdom Panasas
The Nuclear Department at the Defence Academy of the United Kingdom, recently installed ActiveStor 11 to accelerate research. Leveraging PanFS, the integrated
Panasas parallel file system to support a high performance Linux cluster, the academy performs Monte Carlo simulations of whole core reactor behaviors and runs
deterministic models of radiation transport problems.
The Center for High Performance Computing at Utah State University (HPC@USU) provides campus-wide HPC
resources to facilitate world-class research and
scientific discovery. The center relies on Panasas ®
ActiveStor® to provide cost-effective performance, scalability, and ease of use to fuel research excellence
Big data describes the phenomenon of using data to
derive business value. Financial organizations create value
with big data through the collection and simulation of data
for risk analysis, research, and post-trade analytics. The
sheer volume and growth rate of data can strain storage
resources. Monte Carlo simulation, tick data analysis, and
portfolio optimization require high performance parallel
storage to satisfy the demand for fast, shared access to
large and small files alike. This data explosion is driving
the need for fast, extremely scalable, easy to manage, and
affordable high performance storage system
ActiveStor removes performance bottle necks found in traditional NAS systems by allowing the compute clients to read and write data in parallel to and from the physical storage devices, allowing incredibly fast access to very large data sets from many clients, simultaneously. Companies who deploy Panasas storage will dramatically
reduce processing time—improving user productivity and reducing overall project time while simplifying storage operations and management
Data Sheet for Panasas ActiveStor 16.
Hybrid Scale-out NAS Appliance Accelerates Time-to-Resultsfor Technical Research and Enterprise Workloads
Panasas® ActiveStor® with PanFS® 6.0 is the only no-compromise hybrid scale-out NAS solution
designed to deliver performance, reliability and manageability at scale. With flash technology
speeding small file and metadata performance, ActiveStor provides significantly improved
file system responsiveness while accelerating time-to-results. Based on a fifth-generation
storage blade architecture and the Panasas PanFS storage operating system, ActiveStor offers
an attractive low total cost of ownership for the energy, finance, government, life sciences,
manufacturing, media, and university research markets.
Accelerating Design in Manufacturing EnvironmentsPanasas
Panasas parallel storage brings HPC storage features to Computer Aided Engineering (CAE) applications in manufacturing environments. The combination of scalable application software and commodity compute
clusters that leverage Panasas® ActiveStor® scale-out NAS technology has resulted in
significant productivity advantages for CAE workflows. The benefits range from compelling cost/performance improvements
to time-saving, high-fidelity simulation.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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.
Epistemic Interaction - tuning interfaces to provide information for AI support
National Institutes of Health Maximize Computing Resources with Panasas
1. Customer Success Story
National Institutes of Health
L INST
National Institutes of Health
NA The National Center for Biotechnology Information (NCBI), a division of the
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NATIO
UTES
National Library of Medicine (NLM) at the National Institutes of Health (NIH),
F serves as a national resource for molecular biology information serving
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H E A LT
H
research groups from around the world. Established in 1988, NCBI develops
new information technologies to aid in the understanding of fundamental
molecular and genetic processes that control health and disease. NCBI
creates public databases, conducts research in computational biology,
develops software tools for analyzing genomic data, and disseminates
biomedical information. Some 450 people—ranging from NCBI researchers
and staff scientists to programmers, curators, and indexers—generate, store,
and access NCBI databases.
SUMMARY The Challenge Designed specifically to accelerate the
Industry: Researchers at NCBI depend on high- performance of applications deployed
Life Sciences/Government performance compute clusters to run on Linux compute clusters, the Panasas
complex analyses of genotyping and storage cluster effectively eliminated the
THE CHALLENGE sequencing data. The existing storage research-impacting I/O bottlenecks.
Meet demands of researchers from architecture did not effectively scale
around the globe accessing the NCBI to support such efforts as the 1000 PAS storage now provides scalable
public database to conduct genome
Genomes Project, an ambitious endeavor performance and capacity to multiple
research. Eliminate I/O bottlenecks and
maximize computing resources for public to sequence the genomes of at least internal production systems (both Linux-
databases, including an estimated 1.5 1,000 people from around the world. and Windows-based platforms), including
PB of genetic information for the 1000 NCBI’s 1800-core Dell PowerEdge cluster
The project, creating the most detailed
Genomes Project.
and medically useful picture to date of that provides computing resources to some
human genetic variation, is expected to 80 applications used by ten NCBI research
THE SOLUTION groups. Panasas Storage supports much
generate more than 1.5 PB of genetic
PAS Storage system with the PanFSTM information. NCBI will be required to of the daily computation that generates
parallel file system, 1800-core Dell
PowerEdge Cluster, Cisco 6509 archive and provide timely investigator the data for such high-visibility services
Network Switch access to as much as 3 TB of new as NCBI’s PubMed resource that brings
genome data arriving weekly from each of together more than 18 million citations from
THE RESULT the six institutes participating in the 1000 MEDLINE and other life science journals
Genomes Project. To accommodate the for biomedical articles.
• 5X application performance
improvement expected high demand for data access
• Timelier database updates with NCBI requires a storage solution that is Most recently, NCBI implemented a PAS
faster time-to-results reliable, manageable, and affordable. Storage system that provides economical
• High performance irrespective of second-tier storage for the high-density
access patterns/dataset size The Solution data requirements of the 1000 Genomes
• Affordable scalability for fast- NCBI selected Panasas Storage for the Project. The PAS solution also provides
growing archives Center’s Dell PowerEdge compute farm. storage resources to projects such as
• Administrative efficiencies across The decision was based in part on testing the NCBI Short Read Archive (SRA), a
primary and secondary storage
results that indicated the Panasas Storage central repository for short read sequencing
solution delivers a significant performance data, and the dbGaP public repository of
improvement over existing installed storage. genotypes and phenotypes.
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