At this year’s annual Design Automation Conference (DAC 2020), Rob Lalonde and Bill Bryce of Univa partnered with representatives from Google and Synopsys to discuss EDA in the Cloud and share best practices related to cloud migration.
Optimizing Your Cloud Applications in RightScaleRightScale
This document discusses optimizing cloud applications in RightScale. It covers topics like 3-tier application architecture, vertical and horizontal scaling, monitoring with RightScale and New Relic RPM, optimizing database performance, and load testing. Key points include how RightScale supports monitoring through server templates, collected data, and cluster graphs, and how New Relic RPM provides application performance analytics. It also discusses optimizing databases by configuring for instance size, identifying bottlenecks, and monitoring performance metrics and queries.
VMworld 2013: How to Replace Websphere Application Server (WAS) with TCserver VMworld
VMworld 2013
Kaushik Bhattacharya, Pivotal
Michel Bond, VMware
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
This document outlines a utility-based scheduling approach for distributed computing resources. It discusses motivations for improving on existing scheduling techniques, including reducing queue wait times and increasing resource utilization. The design section describes using a partial utility function that considers job priorities, requirements and relaxation levels to make scheduling decisions. The implementation uses Condor middleware and a utility scheduler to dynamically monitor resources and match jobs. Evaluation results show improvements in resource utilization and ability to run more jobs in parallel with reduced completion times compared to default scheduling.
What's new in log insight 3.3 presentationDavid Pasek
This document summarizes new features in VMware vRealize Log Insight 3.3, including enhanced vSphere integration, load balancer capabilities, alert options via webhooks, UI improvements, authentication and query APIs, new log parsers, and additional features. It provides an overview of how vRealize Log Insight can help customers address challenges around monitoring data overload, siloed operations management, cost cutting, and the need for greater operational efficiency.
Evolution of unix environments and the road to faster deploymentsRakuten Group, Inc.
1. In the 1960s, Ken Thompson created the video game "Space Travel" while working on the Multics Operating System at Bell Labs. When Bell Labs withdrew from the project, Thompson rewrote Space Travel on an old PDP-7 machine. The tools created for the game later became the Unix operating system.
2. Virtualization successfully decoupled hardware from services, allowing easy provisioning of virtual machines (VMs) from standard templates. This simplified administration and reduced provisioning time from months to days or immediately.
3. The rise of public cloud and internal virtualization drove the creation of DevOps approaches to fully automate the software development lifecycle from code to deployment. This automation reduced friction
Fusion simulations have traditionally required the use of leadership scale HPC resources in order to produce advances in physics. One such package is CGYRO, a premier tool for multi-scale plasma turbulence simulation. CGYRO is a typical HPC application that will not fit into a single node, as it requires several TeraBytes of memory and O(100) TFLOPS compute capability for cutting-edge simulations. CGYRO also requires high-throughput and low-latency networking, due to its reliance on global FFT computations. While in the past such compute may have required hundreds, or even thousands of nodes, recent advances in hardware capabilities allow for just tens of nodes to deliver the necessary compute power. We explored the feasibility of running CGYRO on Cloud resources provided by Microsoft on their Azure platform, using the infiniband-connected HPC resources in spot mode. We observed both that CPU-only resources were very efficient, and that running in spot mode was doable, with minimal side effects. The GPU-enabled resources were less cost effective but allowed for higher scaling.
Optimizing Your Cloud Applications in RightScaleRightScale
This document discusses optimizing cloud applications in RightScale. It covers topics like 3-tier application architecture, vertical and horizontal scaling, monitoring with RightScale and New Relic RPM, optimizing database performance, and load testing. Key points include how RightScale supports monitoring through server templates, collected data, and cluster graphs, and how New Relic RPM provides application performance analytics. It also discusses optimizing databases by configuring for instance size, identifying bottlenecks, and monitoring performance metrics and queries.
VMworld 2013: How to Replace Websphere Application Server (WAS) with TCserver VMworld
VMworld 2013
Kaushik Bhattacharya, Pivotal
Michel Bond, VMware
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
This document outlines a utility-based scheduling approach for distributed computing resources. It discusses motivations for improving on existing scheduling techniques, including reducing queue wait times and increasing resource utilization. The design section describes using a partial utility function that considers job priorities, requirements and relaxation levels to make scheduling decisions. The implementation uses Condor middleware and a utility scheduler to dynamically monitor resources and match jobs. Evaluation results show improvements in resource utilization and ability to run more jobs in parallel with reduced completion times compared to default scheduling.
What's new in log insight 3.3 presentationDavid Pasek
This document summarizes new features in VMware vRealize Log Insight 3.3, including enhanced vSphere integration, load balancer capabilities, alert options via webhooks, UI improvements, authentication and query APIs, new log parsers, and additional features. It provides an overview of how vRealize Log Insight can help customers address challenges around monitoring data overload, siloed operations management, cost cutting, and the need for greater operational efficiency.
Evolution of unix environments and the road to faster deploymentsRakuten Group, Inc.
1. In the 1960s, Ken Thompson created the video game "Space Travel" while working on the Multics Operating System at Bell Labs. When Bell Labs withdrew from the project, Thompson rewrote Space Travel on an old PDP-7 machine. The tools created for the game later became the Unix operating system.
2. Virtualization successfully decoupled hardware from services, allowing easy provisioning of virtual machines (VMs) from standard templates. This simplified administration and reduced provisioning time from months to days or immediately.
3. The rise of public cloud and internal virtualization drove the creation of DevOps approaches to fully automate the software development lifecycle from code to deployment. This automation reduced friction
Fusion simulations have traditionally required the use of leadership scale HPC resources in order to produce advances in physics. One such package is CGYRO, a premier tool for multi-scale plasma turbulence simulation. CGYRO is a typical HPC application that will not fit into a single node, as it requires several TeraBytes of memory and O(100) TFLOPS compute capability for cutting-edge simulations. CGYRO also requires high-throughput and low-latency networking, due to its reliance on global FFT computations. While in the past such compute may have required hundreds, or even thousands of nodes, recent advances in hardware capabilities allow for just tens of nodes to deliver the necessary compute power. We explored the feasibility of running CGYRO on Cloud resources provided by Microsoft on their Azure platform, using the infiniband-connected HPC resources in spot mode. We observed both that CPU-only resources were very efficient, and that running in spot mode was doable, with minimal side effects. The GPU-enabled resources were less cost effective but allowed for higher scaling.
How to Make Your Move to the Cloud with ConfidenceCloud Spectator
This document discusses how to move to the cloud with confidence by properly evaluating cloud providers and workloads. It recommends:
1) Selecting candidate cloud providers based on requirements like security, locations, compliance and pricing.
2) Benchmarking providers by testing real workloads over time on different machines and comparing performance of infrastructure components and applications.
3) A case study where benchmarking found one provider was 47% cheaper than another for a company after workloads were properly sized based on performance needs. Benchmarking helped optimize costs through performance normalization.
When HPC meet ML/DL: Manage HPC Data Center with KubernetesYong Feng
When HPC Meet ML/DL
Machine learning and deep learning (ML/DL) are becoming important workloads for high performance computing (HPC) as new algorithms are developed to solve business problems across many domains. Container technologies like Docker can help with the portability and scalability needs of ML/DL workloads on HPC systems. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications that can help run MPI jobs and ML/DL pipelines on HPC systems, though it currently lacks some features important for HPC like advanced job scheduling capabilities. Running an HPC-specific job scheduler like IBM Spectrum LSF on top of Kubernetes is one approach to address current gaps in
This document discusses building a disaster recovery solution using OpenStack. It outlines the goals of providing a configurable warm standby solution with a known recovery point objective (RPO) and reduced recovery time objective (RTO) to minimize business impact. The document describes challenges in replicating an application across clouds while preserving the running environment. It provides an overview of the disaster recovery process using OpenStack, including taking snapshots, creating volumes, and mounting new instances. Optimizations discussed include incremental backups and parallel transfers to improve large data transfer speeds across cloud datacenters for disaster recovery.
AWS Sydney Summit 2013 - Technical Lessons on How to do DR in the CloudAmazon Web Services
1. The document discusses backup and disaster recovery (DR) lessons learned from implementing backup and DR solutions using AWS for Ausenco Limited. It provides definitions of archiving, backup, and DR.
2. It then describes Ausenco's IT environment and challenges with unreliable backups, lack of DR, and limited local storage. Their initial approach involved consulting various vendors before shifting to leverage AWS cloud services.
3. The results section outlines key lessons around backup including ensuring it is accessible, able to scale, safe, works with DR policies, and that ownership is clearly defined. For DR, lessons include having a plan, testing regularly, and that different solutions can meet varying needs.
Klepsydra is a software abstraction layer that improves performance of embedded software applications. It transparently interfaces applications with middleware like ROS and DDS. Klepsydra uses techniques like blocking queues and disruptors to optimize message passing. This leads to faster image processing and lower hardware requirements. Klepsydra also improves testing and maintainability. Its business model is freemium, targeting sectors like aerospace, autonomous vehicles, and robotics. Future work includes distributed computing and cloud support.
This document discusses resource management in cloud computing and strategies for improving energy efficiency. It describes different resource types, including physical and logical resources. It then discusses how resource management controls access to cloud capabilities. The document outlines how data center power consumption is growing rapidly and motivating the need for green computing approaches. These include power-aware and thermal-aware scheduling of virtual machines, optimized data center design, and minimizing the size of virtual machine images to reduce energy usage. The overall summary advocates an integrated green cloud framework combining various efficiency techniques.
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Experiences in Delivering Spark as a ServiceKhalid Ahmed
Spark as a service provides fully managed Spark environments on Bluemix that are accessible on-demand for interactive and batch workloads. The architecture involves running Spark clusters for each tenant in a multi-tenant manner with a session scheduler that provides fine-grained resource scheduling and isolation between tenants. This allows Spark to be delivered efficiently as a service while addressing challenges around multi-tenancy, workload management, and enterprise production requirements.
Efficient Resource Allocation to Virtual Machine in Cloud Computing Using an ...ijceronline
The focus of the paper is to generate an advance algorithm of resource allocation and load balancing that can deduced and avoid the dead lock while allocating the processes to virtual machine. In VM while processes are allocate they executes in queue , the first process get resources , other remains in waiting state .As rest of VM remains idle . To utilize the resources, we have analyze the algorithm with the help of First-Come, First-Served (FCFS) Scheduling, Shortest-Job-First (SJR) Scheduling, Priority Scheduling, Round Robin (RR) and CloudSIM Simulator.
Jelastic provides a turnkey Private, Public and Hybrid cloud platform that brings together unlimited PaaS ease of use and container-based IaaS flexibility.
This document discusses observability and how to implement it using logging, metrics, and distributed tracing. It recommends using the three pillars together to gain insights into a distributed system. Spring Boot utilities like Actuator, Micrometer, and Spring Cloud Sleuth can provide much of the functionality out of the box. Centralized logging, metrics collection with Prometheus/Grafana, and distributed tracing with Zipkin are suggested for full observability.
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...Chris Fregly
This document discusses distributed deep learning on the MapR Converged Data Platform. It provides an overview of MapR's enterprise big data journey and capabilities for distributed deep learning. It describes using containers and Kubernetes for deep learning model development and deployment, with NVIDIA GPUs for computation. It presents architectures and patterns for separating or collocating MapR and GPU clusters. Finally, it previews demos of parameter server/workers and real-time face detection using streams.
Track 2, session 4, data protection and disaster recovery with riverbedEMC Forum India
Riverbed provides WAN optimization and data protection solutions using its Steelhead, Cascade, Whitewater, and other products. Whitewater provides a cloud storage gateway that can accelerate backup and recovery to public cloud storage by up to 30x while reducing backup costs by 50% or more. Riverbed has partnerships with EMC and other storage vendors to provide awareness of replication protocols like SRDF, enabling more efficient WAN usage. Customers have reported significant improvements in DR capability and WAN performance for replication workloads without increasing bandwidth using Riverbed solutions.
RightScale Webinar feat. Redapt: How to Build a Private or Hybrid CloudRightScale
Organizations everywhere are looking for the best ways to leverage cloud technologies to maximize efficiencies, minimize costs, and increase agility. Research shows that a majority of enterprises are taking a hybrid cloud approach to leverage existing hardware or to meet performance, compliance, and security requirements.
During this webinar, RightScale and Redapt are teaming up to walk you through private and hybrid cloud environments and share their best practices on evaluating, designing, and deploying a hybrid cloud architecture. We’ll dive into the private cloud aspect and how to build a private cloud to meet your requirements.
You’ll walk away from from this webinar with a fundamental understanding of:
1. Requirements mapping
2. Private cloud hardware considerations
3. Private cloud orchestration software considerations
4. Connecting private and public cloud resources
5. Cloud security
Edge 2016 Session 1886 Building your own docker container cloud on ibm power...Yong Feng
The material for IBM Edge 2016 session for a client use case of Spectrum Conductor for Containers
https://www-01.ibm.com/events/global/edge/sessions/.
Please refer to http://ibm.biz/ConductorForContainers for more details about Spectrum Conductor for Containers.
Please refer to https://www.youtube.com/watch?v=7YMjP6EypqA and https://www.youtube.com/watch?v=d9oVPU3rwhE for the demo of Spectrum Conductor for Containers.
FT Architecture For Cloud Service Computingdestruck
This document summarizes a course on fault tolerant computing in cloud systems. It defines cloud computing and discusses common types of failures that can occur in cloud services, such as overflows, timeouts, and hardware/software failures. It then outlines a proposed fault tolerance framework for cloud computing that uses techniques like fault prediction, process-level redundancy, and checkpoint/restart to minimize overhead and provide transparent fault tolerance without requiring application modifications. The framework also leverages fault prediction, failure detection, and a control daemon to determine when to checkpoint and recover applications.
In this presentation Matt Herreras and Josh Simons describe how Hybrid Cloud powered by virtualization offers increased scientific agility for HPC workloads.
Make no mistake; virtualization is coming to HPC in a Big Way, and everyone will benefit.
Learn more: http://cto.vmware.com/author/joshsimons/
Watch the video presentation: http://wp.me/p3RLHQ-baU
SAP Teched 2012 Session Tec3438 Automate IaaS SAP deploymentsChris Kernaghan
This document summarizes automation of infrastructure as a service deployments and monitoring. It discusses Infrastructure as a Service (IaaS) and how IaaS environments allow for scalable, on-demand provisioning of computing resources. It also discusses SAP's support for AWS and how Capgemini UK uses AWS for SAP deployments. The document advocates for automating infrastructure tasks to improve consistency, auditability and repeatability. It provides examples of automation for build processes, configuration management, change management, exception monitoring, and other areas. Overall, the document promotes automating infrastructure processes in IaaS environments to improve agility, reduce costs, and ensure compliance.
Navops talk at hpc in the cloud meetup 19 march 2019Abhishek Gupta
This document discusses how Univa provides software-defined computing infrastructure solutions to help companies modernize workloads and accelerate hybrid cloud migration. It summarizes Univa's products and capabilities, including:
- Cluster management and workload orchestration software used by 250+ global customers across industries like energy, government, finance, and more.
- Navops Launch, which can deploy and manage hybrid or dedicated HPC clusters across multiple public clouds, and automates all aspects of cloud usage.
- Case studies of companies like Wharton School and Mellanox who were able to avoid infrastructure costs and improve resource utilization by bursting workloads to the cloud using Univa's solutions.
Ask The Architect: RightScale & AWS Dive Deep into Hybrid ITRightScale
With the increased use of cloud services, organizations are faced with finding the most efficient way to use existing IT infrastructure alongside cloud-based compute, storage and networking resources. This has resulted in the rise of hybrid IT whereby companies leverage both on-premises and cloud resources to drive increased agility, stability and accessibility.
How to Make Your Move to the Cloud with ConfidenceCloud Spectator
This document discusses how to move to the cloud with confidence by properly evaluating cloud providers and workloads. It recommends:
1) Selecting candidate cloud providers based on requirements like security, locations, compliance and pricing.
2) Benchmarking providers by testing real workloads over time on different machines and comparing performance of infrastructure components and applications.
3) A case study where benchmarking found one provider was 47% cheaper than another for a company after workloads were properly sized based on performance needs. Benchmarking helped optimize costs through performance normalization.
When HPC meet ML/DL: Manage HPC Data Center with KubernetesYong Feng
When HPC Meet ML/DL
Machine learning and deep learning (ML/DL) are becoming important workloads for high performance computing (HPC) as new algorithms are developed to solve business problems across many domains. Container technologies like Docker can help with the portability and scalability needs of ML/DL workloads on HPC systems. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications that can help run MPI jobs and ML/DL pipelines on HPC systems, though it currently lacks some features important for HPC like advanced job scheduling capabilities. Running an HPC-specific job scheduler like IBM Spectrum LSF on top of Kubernetes is one approach to address current gaps in
This document discusses building a disaster recovery solution using OpenStack. It outlines the goals of providing a configurable warm standby solution with a known recovery point objective (RPO) and reduced recovery time objective (RTO) to minimize business impact. The document describes challenges in replicating an application across clouds while preserving the running environment. It provides an overview of the disaster recovery process using OpenStack, including taking snapshots, creating volumes, and mounting new instances. Optimizations discussed include incremental backups and parallel transfers to improve large data transfer speeds across cloud datacenters for disaster recovery.
AWS Sydney Summit 2013 - Technical Lessons on How to do DR in the CloudAmazon Web Services
1. The document discusses backup and disaster recovery (DR) lessons learned from implementing backup and DR solutions using AWS for Ausenco Limited. It provides definitions of archiving, backup, and DR.
2. It then describes Ausenco's IT environment and challenges with unreliable backups, lack of DR, and limited local storage. Their initial approach involved consulting various vendors before shifting to leverage AWS cloud services.
3. The results section outlines key lessons around backup including ensuring it is accessible, able to scale, safe, works with DR policies, and that ownership is clearly defined. For DR, lessons include having a plan, testing regularly, and that different solutions can meet varying needs.
Klepsydra is a software abstraction layer that improves performance of embedded software applications. It transparently interfaces applications with middleware like ROS and DDS. Klepsydra uses techniques like blocking queues and disruptors to optimize message passing. This leads to faster image processing and lower hardware requirements. Klepsydra also improves testing and maintainability. Its business model is freemium, targeting sectors like aerospace, autonomous vehicles, and robotics. Future work includes distributed computing and cloud support.
This document discusses resource management in cloud computing and strategies for improving energy efficiency. It describes different resource types, including physical and logical resources. It then discusses how resource management controls access to cloud capabilities. The document outlines how data center power consumption is growing rapidly and motivating the need for green computing approaches. These include power-aware and thermal-aware scheduling of virtual machines, optimized data center design, and minimizing the size of virtual machine images to reduce energy usage. The overall summary advocates an integrated green cloud framework combining various efficiency techniques.
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Experiences in Delivering Spark as a ServiceKhalid Ahmed
Spark as a service provides fully managed Spark environments on Bluemix that are accessible on-demand for interactive and batch workloads. The architecture involves running Spark clusters for each tenant in a multi-tenant manner with a session scheduler that provides fine-grained resource scheduling and isolation between tenants. This allows Spark to be delivered efficiently as a service while addressing challenges around multi-tenancy, workload management, and enterprise production requirements.
Efficient Resource Allocation to Virtual Machine in Cloud Computing Using an ...ijceronline
The focus of the paper is to generate an advance algorithm of resource allocation and load balancing that can deduced and avoid the dead lock while allocating the processes to virtual machine. In VM while processes are allocate they executes in queue , the first process get resources , other remains in waiting state .As rest of VM remains idle . To utilize the resources, we have analyze the algorithm with the help of First-Come, First-Served (FCFS) Scheduling, Shortest-Job-First (SJR) Scheduling, Priority Scheduling, Round Robin (RR) and CloudSIM Simulator.
Jelastic provides a turnkey Private, Public and Hybrid cloud platform that brings together unlimited PaaS ease of use and container-based IaaS flexibility.
This document discusses observability and how to implement it using logging, metrics, and distributed tracing. It recommends using the three pillars together to gain insights into a distributed system. Spring Boot utilities like Actuator, Micrometer, and Spring Cloud Sleuth can provide much of the functionality out of the box. Centralized logging, metrics collection with Prometheus/Grafana, and distributed tracing with Zipkin are suggested for full observability.
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...Chris Fregly
This document discusses distributed deep learning on the MapR Converged Data Platform. It provides an overview of MapR's enterprise big data journey and capabilities for distributed deep learning. It describes using containers and Kubernetes for deep learning model development and deployment, with NVIDIA GPUs for computation. It presents architectures and patterns for separating or collocating MapR and GPU clusters. Finally, it previews demos of parameter server/workers and real-time face detection using streams.
Track 2, session 4, data protection and disaster recovery with riverbedEMC Forum India
Riverbed provides WAN optimization and data protection solutions using its Steelhead, Cascade, Whitewater, and other products. Whitewater provides a cloud storage gateway that can accelerate backup and recovery to public cloud storage by up to 30x while reducing backup costs by 50% or more. Riverbed has partnerships with EMC and other storage vendors to provide awareness of replication protocols like SRDF, enabling more efficient WAN usage. Customers have reported significant improvements in DR capability and WAN performance for replication workloads without increasing bandwidth using Riverbed solutions.
RightScale Webinar feat. Redapt: How to Build a Private or Hybrid CloudRightScale
Organizations everywhere are looking for the best ways to leverage cloud technologies to maximize efficiencies, minimize costs, and increase agility. Research shows that a majority of enterprises are taking a hybrid cloud approach to leverage existing hardware or to meet performance, compliance, and security requirements.
During this webinar, RightScale and Redapt are teaming up to walk you through private and hybrid cloud environments and share their best practices on evaluating, designing, and deploying a hybrid cloud architecture. We’ll dive into the private cloud aspect and how to build a private cloud to meet your requirements.
You’ll walk away from from this webinar with a fundamental understanding of:
1. Requirements mapping
2. Private cloud hardware considerations
3. Private cloud orchestration software considerations
4. Connecting private and public cloud resources
5. Cloud security
Edge 2016 Session 1886 Building your own docker container cloud on ibm power...Yong Feng
The material for IBM Edge 2016 session for a client use case of Spectrum Conductor for Containers
https://www-01.ibm.com/events/global/edge/sessions/.
Please refer to http://ibm.biz/ConductorForContainers for more details about Spectrum Conductor for Containers.
Please refer to https://www.youtube.com/watch?v=7YMjP6EypqA and https://www.youtube.com/watch?v=d9oVPU3rwhE for the demo of Spectrum Conductor for Containers.
FT Architecture For Cloud Service Computingdestruck
This document summarizes a course on fault tolerant computing in cloud systems. It defines cloud computing and discusses common types of failures that can occur in cloud services, such as overflows, timeouts, and hardware/software failures. It then outlines a proposed fault tolerance framework for cloud computing that uses techniques like fault prediction, process-level redundancy, and checkpoint/restart to minimize overhead and provide transparent fault tolerance without requiring application modifications. The framework also leverages fault prediction, failure detection, and a control daemon to determine when to checkpoint and recover applications.
In this presentation Matt Herreras and Josh Simons describe how Hybrid Cloud powered by virtualization offers increased scientific agility for HPC workloads.
Make no mistake; virtualization is coming to HPC in a Big Way, and everyone will benefit.
Learn more: http://cto.vmware.com/author/joshsimons/
Watch the video presentation: http://wp.me/p3RLHQ-baU
SAP Teched 2012 Session Tec3438 Automate IaaS SAP deploymentsChris Kernaghan
This document summarizes automation of infrastructure as a service deployments and monitoring. It discusses Infrastructure as a Service (IaaS) and how IaaS environments allow for scalable, on-demand provisioning of computing resources. It also discusses SAP's support for AWS and how Capgemini UK uses AWS for SAP deployments. The document advocates for automating infrastructure tasks to improve consistency, auditability and repeatability. It provides examples of automation for build processes, configuration management, change management, exception monitoring, and other areas. Overall, the document promotes automating infrastructure processes in IaaS environments to improve agility, reduce costs, and ensure compliance.
Navops talk at hpc in the cloud meetup 19 march 2019Abhishek Gupta
This document discusses how Univa provides software-defined computing infrastructure solutions to help companies modernize workloads and accelerate hybrid cloud migration. It summarizes Univa's products and capabilities, including:
- Cluster management and workload orchestration software used by 250+ global customers across industries like energy, government, finance, and more.
- Navops Launch, which can deploy and manage hybrid or dedicated HPC clusters across multiple public clouds, and automates all aspects of cloud usage.
- Case studies of companies like Wharton School and Mellanox who were able to avoid infrastructure costs and improve resource utilization by bursting workloads to the cloud using Univa's solutions.
Ask The Architect: RightScale & AWS Dive Deep into Hybrid ITRightScale
With the increased use of cloud services, organizations are faced with finding the most efficient way to use existing IT infrastructure alongside cloud-based compute, storage and networking resources. This has resulted in the rise of hybrid IT whereby companies leverage both on-premises and cloud resources to drive increased agility, stability and accessibility.
This document provides an overview of cloud computing and testing in the cloud. It discusses key aspects of cloud computing including pay-per-use models, virtual server pools, and various cloud deployment models. It then covers cloud service level agreements and their technical and commercial terms. The document outlines different strategies for testing in the cloud including automation, functional testing, and monitoring. It also discusses challenges like security and reliability and how defects are tracked. Overall the document is providing guidance on testing applications and infrastructure deployed in cloud environments.
10 Key Steps for Moving from Legacy Infrastructure to the CloudNGINX, Inc.
On-demand recording: https://nginx.webex.com/nginx/lsr.php?RCID=af9c355d1f42420b17e048e82ac6762b
Moving your applications from traditional IT stacks to the cloud is not an easy task. Migration to the cloud can cause security nightmares, performance degradation, and sudden cost spikes, to name just a few possible problems. For a successful cloud migration, you need to evolve both technology and business processes.
Nonetheless, moving from legacy infrastructure to public, private, or hybrid cloud can bring massive benefits, including increased flexibility, the ability to scale up or down as needed, and dramatic cost savings. When done well, transforming your business to adopt cloud services can be both painless and profitable.
Please join us for this webinar by James Bond, CTO at Hewlett Packard Enterprise and an expert in cloud computing. He will cover best practices for making your cloud migration successful, including:
* Why your organization should consider a cloud migration
* How to properly plan for cloud deployment
* What approach you should take to ensure security
* How orchestration tools can help achieve efficiency
* How to build cloud native applications to best take advantage of the cloud
Speaker: James Bond, facebook.com/enterprisecloud
James Bond is an expert in cloud computing with over 25 years of experience in the IT industry. He is a true cloud industry pioneer, having created several successful companies, founded business practices, and hosted infrastructure and software services long before the term "cloud computing" was first used. James is a Chief Technologist for Hewlett Packard Enterprise (HPE) providing cloud strategy, guidance, and implementation planning to Fortune 100 organizations that are planning a transition from legacy IT to cloud. He is a featured speaker at industry conferences and executive briefings throughout North America.
This document provides an overview of enterprise cloud transformation best practices. It discusses key aspects of cloud maturity models, alignment of IT and business strategy, agile cloud development practices, and software defined networking (SDN). Specific topics covered include virtualization maturity, cloud brokerage, application lifecycles, and network functions virtualization. Examples from AT&T and Virtela are given to illustrate real-world SDN implementations.
Taming the cost of your first cloud - CCCEU 2014Tim Mackey
Today everyone is talking about clouds, and a few are building them, but far fewer are operating successful clouds. In this session we'll examine a variety of paradigm shifts IT makes when moving from a traditional virtualization and management mindset to operating a successful cloud. For most organizations, without careful planning the hype of a cloud solution can quickly overcome its capabilities and pre-existing best practices can combine to create the worst possible cloud scenario -- a cloud which isn't economical to operate, and which is more cumbersome to manage than a traditional virtualization farm.
Key topics covered include:
- Successful transition of operational and management paradigm
- How the VM density of clouds change Ops
- What it means to monitor the network in a cloud environment, at hyper-dense virtualization levels
- Preventing storage costs from outpacing delivery costs
FInal Project - USMx CC605x Cloud Computing for Enterprises - Hugo AquinoHugo Aquino
The document presents a final project analyzing the potential for a company to migrate its IT infrastructure from an on-premises data center to cloud computing on AWS. It finds that moving to AWS reserved instances could save over $3.5 million versus on-premises costs over 3 years, with a payback period of 14 months. It describes the company's need to scale efficiently and lower costs to support growth. A SWOT analysis and technical feasibility checklists are recommended before fully committing to a cloud migration.
Webinar: Burst ANSYS Workloads to the Cloud with Univa & UberCloudThomas Francis
Univa and UberCloud demonstrate how to manage and execute Ansys Application Containers in a hybrid cloud, powered by Navops Launch and Univa Grid Engine.
UberCloud and Univa have partnered to provide a comprehensive container orchestration environment together with growing set of containerized application software from ANSYS, CD-adapco, Gromacs, NICE DCV, Numeca, OpenFOAM, PSPP, Scilab.
www.theubercloud.com/cloud-hpc
This document discusses high performance computing (HPC) on Microsoft Azure. It begins with an overview of the HPC opportunity in the cloud, highlighting how the cloud provides elasticity and scale to accommodate variable computing demands. It then outlines Azure's value proposition for HPC, including its productive, trusted and hybrid capabilities. The document reviews the various HPC resources available on Azure like VMs, GPUs, and Cray supercomputers. It also discusses solutions for HPC like Azure Batch, Azure Machine Learning Compute, Azure CycleCloud and Avere vFXT. Example industry use cases are provided for automotive, financial services, manufacturing, media/entertainment and oil/gas. The summary reiterates that Azure is uniquely positioned
Migration Recipes for Success - AWS Summit Cape Town 2017 Amazon Web Services
Now that you have earmarked workloads for migration, it's time to look at the various tools and methodologies that are available to help customers shift applications to AWS. This session highlights some of the key AWS tools, services and approaches that organisations are using to successfully migrate to the cloud.
AWS Speaker: Sven Hansen, Solution Architect - Amazon Web Services
Customer Speaker: Pieter Breed – Core Platform Engineer Zoona
Cloud Migration and Portability Best PracticesRightScale
Migrating applications to the cloud requires a clear understanding of both business and technical considerations. In addition, you will want to ensure portability among clouds to avoid lock-in. Here we define technical options for cloud portability and how to assess application suitability for migration.
Data centres don't move to the cloud, applications do. In presentation, we use common sense, commercial triggers to move to the cloud and ask when does a move to cloud make sense and when it doesn't.
Following on, we will discuss in detail how an application CAN move to the cloud and when it should be shot to be put out of its misery.
We'll also talk about money - a LOT since someone has to pay for something. How does cost and complexity relate to cloud adoption planning? etc.
A Successful Journey to the Cloud with Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3mPLIlo
A shift to the cloud is a common element of any current data strategy. However, a successful transition to the cloud is not easy and can take years. It comes with security challenges, changes in downstream and upstream applications, and new ways to operate and deploy software. An abstraction layer that decouples data access from storage and processing can be a key element to enable a smooth journey to the cloud.
Attend this webinar to learn more about:
- How to use Data Virtualization to gradually change data systems without impacting business operations
- How Denodo integrates with the larger cloud ecosystems to enable security
- How simple it is to create and manage a Denodo cloud deployment
Interop ITX: Moving applications: From Legacy to Cloud-to-CloudSusan Wu
Cloud computing provides an array of hosting and service options to fit your overall company strategy. Sometimes a public cloud is your best option and other times your data requirements demand a private cloud. As needs converge, a hybrid solution continues to gain popularity. Developers must consider if their applications might be run on either or both.
Hear about Midokura.com's journey going from the colos to cloud servers to AWS.
Cloud Computing is a term used to refer to a model of network computing where a program or application runs on a connected server or servers rather than a local computing device such as a PC, tablet or Smartphone.
www.ipsrglobal.com
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the CloudCloudera, Inc.
3 Things to Learn About:
*On-premises versus the cloud
*Design & benefits of real-time operational data in the cloud
*Best practices and architectural considerations
Deliver Best-in-Class HPC Cloud Solutions Without Losing Your MindAvere Systems
While cloud computing offers virtually unlimited capacity, harnessing that capacity in an efficient, cost effective fashion can be cumbersome and difficult at the workload level. At the organizational level, it can quickly become chaos.
You must make choices around cloud deployment, and these choices could have a long-lasting impact on your organization. It is important to understand your options and avoid incomplete, complicated, locked-in scenarios. Data management and placement challenges make having the ability to automate workflows and processes across multiple clouds a requirement.
In this webinar, you will:
• Learn how to leverage cloud services as part of an overall computation approach
• Understand data management in a cloud-based world
• Hear what options you have to orchestrate HPC in the cloud
• Learn how cloud orchestration works to automate and align computing with specific goals and objectives
• See an example of an orchestrated HPC workload using on-premises data
From computational research to financial back testing, and research simulations to IoT processing frameworks, decisions made now will not only impact future manageability, but also your sanity.
Cloud Migration Cookbook: A Guide To Moving Your Apps To The CloudNew Relic
The process of building new apps or migrating existing apps to a cloud-based platform is complex. There are hundreds of paths you can take and only a few will make sense for you and your business. Get a step-by-step guide on how to plan for a successful app migration.
Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a utility (like the electricity grid) over a network.[1] At the foundation of cloud computing is the broader concept of converged infrastructure and shared services.
Cloud computing, or in simpler shorthand just "the cloud", also focuses on maximizing the effectiveness of the shared resources. Cloud resources are usually not only shared by multiple users but are also dynamically reallocated per demand. This can work for allocating resources to users. For example, a cloud computer facility that serves European users during European business hours with a specific application (e.g., email) may reallocate the same resources to serve North American users during North America's business hours with a different application (e.g., a web server). This approach should maximize the use of computing power thus reducing environmental damage as well since less power, air conditioning, rackspace, etc. are required for a variety of functions. With cloud computing, multiple users can access a single server to retrieve and update their data without purchasing licenses for different applications.
Cloud computing, or in simpler shorthand just "the cloud", also focuses on maximizing the effectiveness of the shared resources. Cloud resources are usually not only shared by multiple users but are also dynamically reallocated per demand. This can work for allocating resources to users. For example, a cloud computer facility that serves European users during European business hours with a specific application (e.g., email) may reallocate the same resources to serve North American users during North America's business hours with a different application (e.g., a web server). This approach should maximize the use of computing power thus reducing environmental damage as well since less power, air conditioning, rackspace, etc. are required for a variety of functions. With cloud computing, multiple users can access a single server to retrieve and update their data without purchasing licenses for different applications.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
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:
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Univa Presentation at DAC 2020
1. 1
Tutorial & Best Practices:
Running EDA Workloads in the Cloud
Rob Lalonde, VP & GM Cloud
Bill Bryce, VP Products
2. 2
About Univa
• Leader in HPC workload management
• 250 global customers
• Hybrid, dedicated, private clouds
• 3.3M+ cores under management
• EDA, Manufacturing, Life Sciences, Oil & Gas,
Government, Research & Edu, Transportation
• Trusted by leading manufacturers
3. 3
Key Focus area: Optimize cloud workloads
• Accelerate regression testing with high-
throughput workload scheduling
• Share resources optimally between diverse
workloads and different design efforts
• Maximize EDA license utilization with license
orchestration software
Advanced workload management and
resource sharing
Cloud migration, automation, and
spend management
• Easily extend on-prem environments to the
cloud to meet peak-demand
• Deploy cloud resources optimally for each
simulation, place workloads correctly
• Maximize the efficiency of cloud resource
usage with automation and spend mgmt.
4. 4
2019 Univa InsideHPC cloud survey results
92%
Using or open to
HPC cloud - up
50% from 2017
64%
Say cloud has
proven value
or high
potential
See value in cloud
spend association
What we spend
BUT
76%
Have no
automated
solution
27%
Need help
27%
Manual
22%
Other
84%
< $10K
$10k to $100k
> $100k
27%
50%
34%
Dedicated
20%
Hybrid
47%
Both
Dedicated or Hybrid Cloud?
31%
In production
SLURM and Grid Engine represent
the majority of HPC cloud workloads
SLURM or
Grid Engine
54%
77%
Spend
monthly
8%
Power Users
75%
Univa sponsored survey – 2019 InsideHPC: Cloud Adoption for HPC: Trends and Opportunities
https://insidehpc.com/white-paper/cloud-adoption-for-hpc-trends-and-opportunities/
5. 5
What customers tell us
• Increasing design complexity, higher gate counts
• Need for higher quality & reliability driving coverage requirements
IoT, SoC embedded, medical devices, etc.
• Shorter product cycles, time-to-market
• Many simulation types: analog, digital, functional, system-level,
multi-physics, ML
• Need to maximize EDA tool utilization
• Limited data center capacity and IT budgets
More than any other industry, EDA users are
continuously challenged to do more with less
6. 6
A typical design environment
Interactive
users
License Server(s)
FlexNet Publisher
Project A
Project B
Project C
EDA Software
Licenses
License sharing
policies
General-
purpose
simulation
High-
throughput
servers
Place and
route
servers
Workload Management
Univa License
Orchestrator
Cloud InstancesOn-premise Infrastructure
Managed network, uniform DNS name-space Managed network, uniform DNS name-space
Cloud
APIs
• Gate Level Simulations (GLS)
• Register Transfer Level Simulations
• Transistor Level Modeling (TLM)
• Physical Verification
• Dynamic IR analysis
• Placement and clock optimization
• Static Timing Analysis (STA)
• Circuit Simulation
• Routing
Instance Provisioning
7. 7
Use case #1: Cloud automation
Boost license utilization, reduce Capex
• EDA environments frequently have “bursty
workloads” – overlapping projects, different
resources requirements at different phases
• For cloud to be practical, cloud provisioning
needs to be automated and transparent to users
• “Bring-your-own-image” functionality (BYOI) for
straightforward cloud migration
• Automate runtime decisions to avoid
administrator effort and potential human error
• Maximize EDA license utilization to improve
overall productivity
CHALLENGE:
• Bursty simulation & verification workloads
• Need to defer/reduce CapEx
• On-premise cluster right sized for day-to-day workloads
• On-premise EDA licenses underutilized
SOLUTION:
• Hybrid Cloud – Navops Launch, Univa Grid Engine
• Auto-scale cloud capacity based on workloads
• Automated data migration to and from the cloud
• Analytics and license management
BUSINESS VALUE:
• Avoid bottlenecks during critical tapeout periods
• Reduce costs - pay for cloud when needed
• Maximize on-premise license usage by shifting non-
licensed work to the cloud improving overall productivity,
Details at: https://blogs.univa.com/2020/01/mission-is-possible-
tips-on-building-a-million-core-cluster/
8. 8
Use case #2: Cloud simulation at extreme scale
Deploying a 1M+ vCPU cluster
• EDA verification and regression tests can run for
days accounting for approx. 80% of workloads
• Cloud capacity can dramatically reduce runtime
• Benefits: Reduced cycle time, more thorough
verification, higher quality, reduced schedule risk
• Many technical challenges solved: checkpointing,
reclaim rates, container registries, API calls etc.
CHALLENGE:
• Engineering design for next-gen hard disk drives
• Requires complex multi-physics simulations
• 2.5 million tasks require days on premise
• Need capacity for more complex designs
SOLUTION:
• Navops Launch – deployed 1M+ vCPU cluster in 90 mins
• 40,000 cloud instances, instances come and go
• Leveraged containerized workloads
• Lower costs with preemptible VMs, spot fleets
BUSINESS VALUE:
• ~60x reduction in runtime – 20 days to 8 hours
• Estimated 50% cost reduction vs on-prem resources
• Increased capacity for new product development
Details at: https://blogs.univa.com/2020/01/mission-is-possible-
tips-on-building-a-million-core-cluster/
9. 9
Use case #3: Optimize cloud instance selection
• Different tools have different requirements
• For licensed tools, it can be more economical to
underutilize machine resources!
• Optimizing selection is a function of license and
instance costs, and tool performance
40
60
80
100
120
140
160
180
200
1 2 3 4 5 6 7 8
Timepersimulation(s)
Simultaneous simulations per cloud instance
Instance A
Instance B
Where should we operate?
2 sims on instance A provides 37%
better throughput but requires 4x the
number of machine instances
compared to 8 sims on instance B
• Topology-aware placement yields further gains
(reducing simulation time, improving efficiency)
• Place workloads for socket/core affinity,
maximize cache per sim, NUMA considerations,
distribute load across memory & I/O channels
S C T T C T T C T T C T T C T T C T T C T T C T T
Example: AMD ROME EPYC 7Fx2 processor –Google Cloud N2D VMs
Closely controlling placement on VM drives greater efficiency
COMMON CHALLENGES FOR EDA SITES:
• Need reporting and license analytics to optimize selection
• Need smart policy-based instance selection at runtime
• Need granular resource scheduling / job placement
Instance selection Workload placement
10. 10
Use case #4: Share resources, manage spending
Share infrastructure and licenses
• Multiple project teams, multiple clusters
• Limited EDA feature licenses
• Need to allocate on-prem/cloud resources and
license features based on configurable policies
• Need to track actual cloud-spending and license
consumption by cost-center /project
• Automated mechanisms to throttle cloud
spending when budgets are exceeded
Manage cloud spend
SERVER MANAGED
LICENSES
FLEXERA
Publisher #1
FLEXERA
Publisher #1
Users
Cluster
LO CONNECTOR
Users
Cluster
LO CONNECTOR
Users
Cluster
LO CONNECTOR
(and additional
Tools)
11. 11
Summary
• Cloud can provide significant additional capacity to speed regression
tests and other EDA workloads
• The key to making cloud cost-efficient is automation, efficient
provisioning, and minimizing impact on existing applications
• Operating at scale requires specific software features for provisioning
and scheduling – it’s challenging to keep cloud-scale clusters busy!
• Placing workloads optimally is key to maximizing the use of EDA
licenses and improving overall throughput and efficiency
• Cloud spend association & management is critical – many
organizations lack automated mechanisms to track and control
spending