themidgame-tube-slides

High Performance Cloud Computing

Deepak Singh

Dad i want a supercomputer on my nextAkash Sahoo

AWS Webcast - Cost and Performance Optimization in Amazon RDS

Amazon RDS makes it easy to set up, operate, and scale relational databases in the cloud. The service offers a variety of options for optimizing the performance level delivered, as well as optimizing your spending. In this webinar, we will show a variety of techniques for implementing the right performance level for your application. Learning Objectives: • Understand the Amazon RDS options that change database performance and cost • Select the appropriate performance and cost level for your specific application Who Should Attend: • Technical Amazon RDS customers and prospective customers

CuPy v4 and v5 roadmap

From the 2017 HPCC Systems Community Day: Amazon Web Services (AWS) is the premier IaaS provider. It leads the pack by offering more and better services at lower prices. Furthermore, AWS continuously improves and innovates to stay in front. There are numerous reasons to use an IaaS for HPCC Systems instead of dedicated hardware, especially if the workload does not execute 24/7. AWS has developed several features and tools for launching clusters. CloudFormation provides users a tool to make creating and managing an AWS resources much easier. Foremost it consists of a template (CFT) that defines resources required. The template is parameterizable and flexible so that a single CFT can launch an HPCC Systems cluster with an arbitrary number of nodes, various amount of memory per node, and other configuration options. Second, an Amazon Machine Image (AMI) contains the information needed to launch a compute node, with appropriate software, and configure it for a specific operation. We developed a CFT and an AMI for HPCC Systems. Additionally, we developed a reference architecture for HPCC Systems in AWS. It is a typical N+1 cluster, N worker nodes and one node (or mode) for cluster wide services such as Dali. The architecture also has storage (i.e., EBS volumes) and networking (i.e., VPN) resources. Significant effort was expended to determine the best set of resources for HPCC Systems clusters. Furthermore, we created a program to create and manage HPCC Systems clusters in AWS from the command line. This talk will present the tools we created. It also explains and justifies the reference architecture and many of the configuration options. Vince Freeh Associate Professor, North Carolina State University Vincent W. Freeh is an associate professor of computer science at North Carolina State University. He received his Ph.D. in 1996 from the University of Arizona. His research focus is high-performance system software, with emphasis on filesystems, parallel and distributed systems, power-aware computing, and storage systems. Prof Freeh teaches courses in the above research areas as well as in compilers. He has more than 55 referred publications in numerous computer science conferences and scientific journals. He received an NSF CAREER Award and several IBM Faculty Development Awards. He was a captain in the US Army Corps of Engineers before entering graduate school for his MS. Chin-Jung Hsu PhD Student, North Carolina State University Chin-Jung Hsu is a Ph.D. candidate in Computer Science at North Carolina State University. His primary research interests include distributed systems, storage systems, and performance optimization. He interned at NetApp and AT&T Research Lab, where he applied machine learning techniques to distributed storage systems for ensuring performance guarantees. Chin-Jung is currently working on how to efficiently run HPCC Systems applications on the public clouds such as AWS and Azure.

Building maps for apps in the cloud - a Softlayer Use Case

Timan Rebel

Deep Dive on Amazon EC2

Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.

Enhance! Real-time webcam video super-resolution

Edward Kim

Gx4

06.09.2017 Computer Science, Machine Learning & Statistiks Meetup - MULTI-GPU...

Zalando adtech lab

Amazon RDS for MySQL – Diagnostics, Security, and Data Migration (DAT302) | A...

Learn how to monitor your database performance closely and troubleshoot database issues quickly using a variety of features provided by Amazon RDS and MySQL including database events, logs, and engine-specific features. You also learn about the security best practices to use with Amazon RDS for MySQL. In addition, you learn about how to effectively move data between Amazon RDS and on-premises instances. Lastly, you learn the latest about MySQL 5.6 and how you can take advantage of its newest features with Amazon RDS.

AWS RDS Benchmark - CMG Brasil 2012

Rodrigo Campos

Agx 2

Tokyo Institute of Technology

 NF5288M5(AGX-2) NF5288M5 is a 2U two-sockets rack server consists 8 NVLink GPU or 8PCIe GPU which is specially designed for AI/HPC • Highest Density: 8 FHFL GPU get emerged in the limited space of 2U chassis • Highest Performance: support the latest optimized NVLink2.0 with fully connection topology, up to 960 Tensor FLOPs and 376 TOPS on INT8. • Highest Flexibility: abundant topology for GPU to meet different work load, free to choose different GPUs. Application scenarios: • AI field----Intelligent Security, Intelligent Traffic, Intelligent Finance, Intelligent Medical and Intelligent Manufacture that need data analysis and training • HPC------High performance clusters pursuing ultra-high performances, such as rendering operation, CAD and CAE. • Video acceleration------Complex and diverse video processing that need paralleled operation for government, education.

Applying Recursive Temporal Blocking for Stencil Computations to Deeper Memor...

Bruno Silva - eMedLab: Merging HPC and Cloud for Biomedical Research

Danny Abukalam

(PFC302) Performance Benchmarking on AWS | AWS re:Invent 2014

In this session, we explain how to measure the key performance-impacting metrics in a cloud-based application and best practices for a reliable benchmarking process. Measuring the performance of applications correctly can be challenging and there are many tools available to measure and track performance. This session will provide you with specific examples of good and bad tests. We make it clear how to get reliable measurements of and how to map benchmark results to your application. We also cover the importance of selecting tests wisely, repeating tests, and measuring variability. In addition a customer will provide real-life examples of how they developed their application testing stack, utilize it for repeatable testing and identify bottlenecks.

Threading Successes 04 Hellgateguest40fc7cd

Intel optimized tensorflow, distributed deep learning

geetachauhan

20180926 kubeflow-meetup-1-kubeflow-operators-Preferred Networks-Shingo Omura

機械学習アプリをKubernetesを用いて管理可能にすることを目的としたKubeflowプロジェクトで開発されている、機械学習ジョブをKubernetesへの展開を容易にするためのOperator群について解説します。【訂正】スライド16において、PyTorch, Caffe2がParameter Server Styleとして記述されていますが、正しくはAllReduce Styleのです。

Cloud Friendly Hadoop and HiveDataWorks Summit

Whirr devdown

Puppet

Cassandra Performance Benchmark

Bigstep

The Economics of Scaling Cassandra - By Alex Bordei, Techie Product Manager at Bigstep This presentation was made during the "Cassandra Summit 2014" Event, in London. We benchmarked Cassandra on a number of configurations and we show what's the scaling profile. We test Cassandra on Docker as well as Cassandra's In-memory feature. Follow Alex on Twitter: @alexandrubordei Bigstep on Twitter: @BigStepInc If you have any questions, let us know at hello@bigstep.com and we'll do our best to answer. Stay informed: http://blog.bigstep.com/

(SDD401) Amazon Elastic MapReduce Deep Dive and Best Practices | AWS re:Inven...

Amazon Elastic MapReduce is one of the largest Hadoop operators in the world. Since its launch five years ago, AWS customers have launched more than 5.5 million Hadoop clusters. In this talk, we introduce you to Amazon EMR design patterns such as using Amazon S3 instead of HDFS, taking advantage of both long and short-lived clusters and other Amazon EMR architectural patterns. We talk about how to scale your cluster up or down dynamically and introduce you to ways you can fine-tune your cluster. We also share best practices to keep your Amazon EMR cluster cost efficient.

What's New in H2O Driverless AI? - Arno Candel - H2O AI World London 2018

Sri Ambati

This talk was recorded in London on Oct 30, 2018 and can be viewed here: https://youtu.be/tNK3Fc02jj0 Arno Candel is the Chief Technology Officer at H2O.ai. He is the main committer of H2O-3 and Driverless AI and has been designing and implementing high-performance machine-learning algorithms since 2012. Previously, he spent a decade in supercomputing at ETH and SLAC and collaborated with CERN on next-generation particle accelerators. Arno holds a PhD and Masters summa cum laude in Physics from ETH Zurich, Switzerland. He was named “2014 Big Data All-Star” by Fortune Magazine and featured by ETH GLOBE in 2015. Follow him on Twitter: @ArnoCandel.

Building an Amazon Datawarehouse and Using Business Intelligence Analytics Tools

Using AWS has never been easier or more affordable to solve business problems and uncover new opportunities using data. Now, businesses of all sizes and across all industries can take advantage of big data technologies and easily collect, store, process, analyze, and share their data. Gain a thorough understanding of what AWS offers across the big data lifecycle and learn architectural best practices for applying these technologies to your projects. We will also deep dive into how to use AWS services such as Kinesis, DynamoDB, Redshift, and Quicksight to optimize logging, build real-time applications, and analyze and visualize data at any scale.

How to run your Hadoop Cluster in 10 minutes

Vladimir Simek

What's hot

HaaS: HPCC Systems as a Service – BYOD to the Cloud Party

HPCC Systems

Building maps for apps in the cloud - a Softlayer Use Case

Timan Rebel

Deep Dive on Amazon EC2

Enhance! Real-time webcam video super-resolution

Edward Kim

Gx4

06.09.2017 Computer Science, Machine Learning & Statistiks Meetup - MULTI-GPU...

Zalando adtech lab

Amazon RDS for MySQL – Diagnostics, Security, and Data Migration (DAT302) | A...

AWS RDS Benchmark - CMG Brasil 2012

Rodrigo Campos

Agx 2

Tokyo Institute of Technology

Applying Recursive Temporal Blocking for Stencil Computations to Deeper Memor...

Bruno Silva - eMedLab: Merging HPC and Cloud for Biomedical Research

Danny Abukalam

(PFC302) Performance Benchmarking on AWS | AWS re:Invent 2014

Threading Successes 04 Hellgateguest40fc7cd

Intel optimized tensorflow, distributed deep learning

geetachauhan

20180926 kubeflow-meetup-1-kubeflow-operators-Preferred Networks-Shingo Omura

Cloud Friendly Hadoop and HiveDataWorks Summit

Whirr devdown

Puppet

Cassandra Performance Benchmark

Bigstep

What's hot (18)

HaaS: HPCC Systems as a Service – BYOD to the Cloud Party

Building maps for apps in the cloud - a Softlayer Use Case

Deep Dive on Amazon EC2

Enhance! Real-time webcam video super-resolution

Gx4

06.09.2017 Computer Science, Machine Learning & Statistiks Meetup - MULTI-GPU...

Amazon RDS for MySQL – Diagnostics, Security, and Data Migration (DAT302) | A...

AWS RDS Benchmark - CMG Brasil 2012

Agx 2

Applying Recursive Temporal Blocking for Stencil Computations to Deeper Memor...

Bruno Silva - eMedLab: Merging HPC and Cloud for Biomedical Research

(PFC302) Performance Benchmarking on AWS | AWS re:Invent 2014

Threading Successes 04 Hellgate

Intel optimized tensorflow, distributed deep learning

20180926 kubeflow-meetup-1-kubeflow-operators-Preferred Networks-Shingo Omura

Cloud Friendly Hadoop and Hive

Whirr devdown

Cassandra Performance Benchmark

Similar to themidgame-tube-slides

(SDD401) Amazon Elastic MapReduce Deep Dive and Best Practices | AWS re:Inven...

What's New in H2O Driverless AI? - Arno Candel - H2O AI World London 2018

Sri Ambati

Building an Amazon Datawarehouse and Using Business Intelligence Analytics Tools

How to run your Hadoop Cluster in 10 minutes

Vladimir Simek

Sizing MongoDB on AWS with Wired Tiger-Patrick and Vigyan-FinalVigyan Jain

Galaxy CloudMan performance on AWS

Enis Afgan

The future of tape

Josef Weingand

Red Hat Storage Day New York - New Reference Architectures

Red_Hat_Storage

Running Apache Spark on a High-Performance Cluster Using RDMA and NVMe Flash ...

Databricks

Effectively leveraging fast networking and storage hardware (e.g., RDMA, NVMe, etc.) in Apache Spark remains challenging. Current ways to integrate the hardware at the operating system level fall short, as the hardware performance advantages are shadowed by higher layer software overheads. This session will show how to integrate RDMA and NVMe hardware in Spark in a way that allows applications to bypass both the operating system and the Java virtual machine during I/O operations. With such an approach, the hardware performance advantages become visible at the application level, and eventually translate into workload runtime improvements. Stuedi will demonstrate how to run various Spark workloads (e.g, SQL, Graph, etc.) effectively on 100Gbit/s networks and NVMe flash.

Re invent 2018 meetup presentation

Eliran Yamin

Lessons learned scaling big data in cloud

Vijay Rayapati

IBM Tape Update Dezember18 - TS1160

Josef Weingand

AWS Webcast - Amazon Elastic Map Reduce Deep Dive and Best Practices

Amazon Elastic MapReduce (EMR) is one of the largest Hadoop operators in the world. Since its launch five years ago, our customers have launched more than 15 million Hadoop clusters inside of EMR. In this webinar, we introduce you to Amazon EMR design patterns such as using Amazon S3 instead of HDFS, taking advantage of both long and short-lived clusters and other Amazon EMR architectural patterns. We talk about how to scale your cluster up or down dynamically and introduce you to ways you can fine-tune your cluster. We also share best practices to keep your Amazon EMR cluster cost efficient.

GPU cloud with Job scheduler and Container

Andrew Yongjoon Kong

Getting Started with Amazon Redshift

Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all of your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing, scale-out architecture, and columnar direct-attached storage to minimize I/O time and maximize performance. Learn how you can gain deeper business insights and save money and time by migrating to Amazon Redshift. Take away strategies for migrating from on-premises data warehousing solutions, tuning schema and queries, and utilizing third party solutions.

Drizzle—Low Latency Execution for Apache Spark: Spark Summit East talk by Shi...

Spark Summit

Drizzle is a low latency execution engine for Apache Spark that is targeted at stream processing and iterative workloads. Currently, Spark uses a BSP computation model, and notifies the scheduler at the end of each task. Invoking the scheduler at the end of each task adds overheads and results in decreased throughput and increased latency. In Drizzle, we introduce group scheduling, where multiple batches (or a group) of computation are scheduled at once. This helps decouple the granularity of task execution from scheduling and amortize the costs of task serialization and launch. Our experiments on a 128 node EC2 cluster show that Drizzle can achieve end-to-end streaming latencies of less than 100ms and can get up to 3.5x lower latency than Spark Streaming. Compared to Apache Flink, a record-at-a-time streaming system, we show that Drizzle can recover around 4x faster from failures and that Drizzle has up to 13x lower latency during recovery.

Cs264 intro-to-cloud-computing

kartiko edhi

[Harvard CS264] 08a - Cloud Computing, Amazon EC2, MIT StarCluster (Justin Ri...

npinto

Putting Kafka Together with the Best of Google Cloud Platform

confluent

(Kir Titievsky, Google) Kafka Summit SF 2018 In this talk we will share some stories and patterns from customers who have built streaming pipelines and event-driven systems using Confluent Cloud in combination with Google Cloud Platform-native analytics tools, such as BigQuery and Dataflow. We will discuss what Confluent Cloud enables for hybrid deployments and how and why to mix and match platform-native and platform-neutral tools.

Day of Cloud: Amazon EC2

cmcavoy

Similar to themidgame-tube-slides (20)

(SDD401) Amazon Elastic MapReduce Deep Dive and Best Practices | AWS re:Inven...

What's New in H2O Driverless AI? - Arno Candel - H2O AI World London 2018

Building an Amazon Datawarehouse and Using Business Intelligence Analytics Tools

How to run your Hadoop Cluster in 10 minutes

Sizing MongoDB on AWS with Wired Tiger-Patrick and Vigyan-Final

Galaxy CloudMan performance on AWS

The future of tape

Red Hat Storage Day New York - New Reference Architectures

Running Apache Spark on a High-Performance Cluster Using RDMA and NVMe Flash ...

Re invent 2018 meetup presentation

Lessons learned scaling big data in cloud

IBM Tape Update Dezember18 - TS1160

AWS Webcast - Amazon Elastic Map Reduce Deep Dive and Best Practices

GPU cloud with Job scheduler and Container

Getting Started with Amazon Redshift

Drizzle—Low Latency Execution for Apache Spark: Spark Summit East talk by Shi...

Cs264 intro-to-cloud-computing

[Harvard CS264] 08a - Cloud Computing, Amazon EC2, MIT StarCluster (Justin Ri...

Putting Kafka Together with the Best of Google Cloud Platform

Day of Cloud: Amazon EC2

Recently uploaded

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.

Knowledge engineering: from people to machines and back

Elena Simperl

From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...

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.

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.

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.

Mission to Decommission: Importance of Decommissioning Products to Increase E...

ODC, Data Fabric and Architecture User Group

CatarinaPereira64715

De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...

FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf

FIDO Alliance

State of ICS and IoT Cyber Threat Landscape Report 2024 preview

Prayukth 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/

The Art of the Pitch: WordPress Relationships and Sales

Laura Byrne

Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes? All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.

The Future of Platform Engineering

Jemma Hussein Allen

Epistemic Interaction - tuning interfaces to provide information for AI support

Alan 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.

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf

91mobiles

Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...

UiPathCommunity

💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™: See how to accelerate model training and optimize model performance with active learning Learn about the latest enhancements to out-of-the-box document processing – with little to no training required Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath. Speakers: 👨‍🏫 Andras Palfi, Senior Product Manager, UiPath 👩‍🏫 Lenka Dulovicova, Product Program Manager, UiPath

To Graph or Not to Graph Knowledge Graph Architectures and LLMs

Paul Groth

AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...