3 approaches to memory protection are as follows:
Memory safe language: Writing modules in memory safe language like Rust automatically manages memory but already there are NF’s written in C/C++ , rewriting them from scratch with Rust will takes lots of effort.
Hardware-based memory protection(fine-grained approach): overhead of MPX comes from loading/storing the individual bounds for every pointers in a program
Coarse-grained hardware protection: Divides memory space into modules based on tenancy , having 2 advantages:
Tenants cant access each other modules and reduces the size of bound table thus reducing lookup overhead.
Conventional architectures coarsely comprise of a processor, memory system, and the datapath.
Each of these components present significant performance bottlenecks.
Parallelism addresses each of these components in significant ways.
Different applications utilize different aspects of parallelism - e.g., data itensive applications utilize high aggregate throughput, server applications utilize high aggregate network bandwidth, and scientific applications typically utilize high processing and memory system performance.
It is important to understand each of these performance bottlenecks.
the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation Used in order to solve large problems in science, engineering, or business.
An explicitly parallel program must specify concurrency and interaction between concurrent subtasks.
The former is sometimes also referred to as the control structure and the latter as the communication model.
Load balancing In cloud - In a semi distributed systemAchal Gupta
Load Balancing in Cloud
What is load balancing in Cloud in semi distributed system and why it is better than a centralized system and distributed system
An introduction to the Design of Warehouse-Scale ComputersAlessio Villardita
A brief overview of the main factors involved in the design of Warehouse-Scale Computers (WSC), from the hardware, to the cooling system to the overall plant energy efficiency, always keeping in mind the costs of such a big architecture.
Co-Author: Pietro Piscione (https://www.linkedin.com/pub/pietro-piscione/84/b37/926)
A work based on:
"The Datacenter as a Computer, An Introduction to the Design of Warehouse-Scale Machines, Second Edition"
by
Luiz André Barroso
Jimmy Clidaras
Urs Hölzle
Conventional architectures coarsely comprise of a processor, memory system, and the datapath.
Each of these components present significant performance bottlenecks.
Parallelism addresses each of these components in significant ways.
Different applications utilize different aspects of parallelism - e.g., data itensive applications utilize high aggregate throughput, server applications utilize high aggregate network bandwidth, and scientific applications typically utilize high processing and memory system performance.
It is important to understand each of these performance bottlenecks.
the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation Used in order to solve large problems in science, engineering, or business.
An explicitly parallel program must specify concurrency and interaction between concurrent subtasks.
The former is sometimes also referred to as the control structure and the latter as the communication model.
Load balancing In cloud - In a semi distributed systemAchal Gupta
Load Balancing in Cloud
What is load balancing in Cloud in semi distributed system and why it is better than a centralized system and distributed system
An introduction to the Design of Warehouse-Scale ComputersAlessio Villardita
A brief overview of the main factors involved in the design of Warehouse-Scale Computers (WSC), from the hardware, to the cooling system to the overall plant energy efficiency, always keeping in mind the costs of such a big architecture.
Co-Author: Pietro Piscione (https://www.linkedin.com/pub/pietro-piscione/84/b37/926)
A work based on:
"The Datacenter as a Computer, An Introduction to the Design of Warehouse-Scale Machines, Second Edition"
by
Luiz André Barroso
Jimmy Clidaras
Urs Hölzle
As more and more workloads move off dedicated hardware into the cloud as virtual appliances, contention for shared hardware resource such as cache, memory and network bandwidth affects performance in the same vein as resources such as CPU and RAM. In this talk we discuss the Resource Management Daemon (RMD) architecture, components, and the design of monitor component that will track and fine tune allocations to meet service level agreements. Last but not least we share how RMD can be leveraged by cloud and container orchestration engines to effectively introduce cache allocation capabilities.
In this webinar, we'll discuss the different ways to back up and restore your single servers, replica sets, and sharded clusters in case of a disaster scenario. We'll review various approaches, including taking filesystem snapshots, using mongodump and mongorestore, or leveraging MongoDB Management Service to backup and restore.
Dr. Konstantinos Giannoutakis presents the CloudLightning simulator, a bespoke cloud simulation engine built for modelling and simulating heterogeneous resources as well as self-organising systems.
This presentation was given at the CloudLightning Conference held in conjunction with NC4 2017 in Dublin City University on 11th April 2017.
Super, Mainframe computers are not cost effective
Cluster technology have been developed that allow multiple low cost computers to work in coordinated fashion to process applications.
Parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has been employed for many years, mainly in high-performance computing, but interest in it has grown lately due to the physical constraints preventing frequency scaling. As power consumption (and consequently heat generation) by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors.
As more and more workloads move off dedicated hardware into the cloud as virtual appliances, contention for shared hardware resource such as cache, memory and network bandwidth affects performance in the same vein as resources such as CPU and RAM. In this talk we discuss the Resource Management Daemon (RMD) architecture, components, and the design of monitor component that will track and fine tune allocations to meet service level agreements. Last but not least we share how RMD can be leveraged by cloud and container orchestration engines to effectively introduce cache allocation capabilities.
In this webinar, we'll discuss the different ways to back up and restore your single servers, replica sets, and sharded clusters in case of a disaster scenario. We'll review various approaches, including taking filesystem snapshots, using mongodump and mongorestore, or leveraging MongoDB Management Service to backup and restore.
Dr. Konstantinos Giannoutakis presents the CloudLightning simulator, a bespoke cloud simulation engine built for modelling and simulating heterogeneous resources as well as self-organising systems.
This presentation was given at the CloudLightning Conference held in conjunction with NC4 2017 in Dublin City University on 11th April 2017.
Super, Mainframe computers are not cost effective
Cluster technology have been developed that allow multiple low cost computers to work in coordinated fashion to process applications.
Parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has been employed for many years, mainly in high-performance computing, but interest in it has grown lately due to the physical constraints preventing frequency scaling. As power consumption (and consequently heat generation) by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors.
DPDK Summit 2015 - Aspera - Charles ShiflettJim St. Leger
DPDK Summit 2015 in San Francisco.
Presentation by Charles Shiflett, Aspera.
For additional details and the video recording please visit www.dpdksummit.com.
The paper includes a study of the most recent prefetching techniques developed for modern day processors, classifying them based on different criteria and performing a qualitative and quantitative evaluation of their performance. It also includes evaluation of the performance of compiler based data prefetching scheme using the built-in prefetcher of gcc compiler.
Approximation techniques used for general purpose algorithmsSabidur Rahman
Survey on approximation techniques used for general purpose algorithms, data parallel applications ans solid-state memories. It is interesting to see how approximation algorithms can contribute to solve real-life problems with better efficiency and lower cost!
Questions? krahman@ucdavis.edu.
HPC and cloud distributed computing, as a journeyPeter Clapham
Introducing an internal cloud brings new paradigms, tools and infrastructure management. When placed alongside traditional HPC the new opportunities are significant But getting to the new world with micro-services, autoscaling and autodialing is a journey that cannot be achieved in a single step.
Some vignettes and advice based on prior experience with Cassandra clusters in live environments. Includes some material from other operational slides.
Your Linux AMI: Optimization and Performance (CPN302) | AWS re:Invent 2013Amazon Web Services
Your AMI is one of the core foundations for running applications and services effectively on Amazon EC2. In this session, you'll learn how to optimize your AMI, including how you can measure and diagnose system performance and tune parameters for improved CPU and network performance. We'll cover application-specific examples from Netflix on how optimized AMIs can lead to improved performance.
Webinar: OpenEBS - Still Free and now FASTEST Kubernetes storageMayaData Inc
Webinar Session - https://youtu.be/_5MfGMf8PG4
In this webinar, we share how the Container Attached Storage pattern makes performance tuning more tractable, by giving each workload its own storage system, thereby decreasing the variables needed to understand and tune performance.
We then introduce MayaStor, a breakthrough in the use of containers and Kubernetes as a data plane. MayaStor is the first containerized data engine available that delivers near the theoretical maximum performance of underlying systems. MayaStor performance scales with the underlying hardware and has been shown, for example, to deliver in excess of 10 million IOPS in a particular environment.
Uncovering Bugs in P4 Programs with Assertion-based VerificationAJAY KHARAT
P4 programs allows Network Administrators to deploy network functionalities.
P4 Programming language allows Network Administrators to specify conditions in few instructions as compared to other programming languages.
Earlier, some tools were developed to detect bugs in P4 programs.
But the proposed models are either not able to model P4 programs or cannot reason about program specifications.
SDPROBER: A SOFTWARE DEFINED PROBER FOR SDNAJAY KHARAT
Showing how the central control in SDN can be used for reducing the costs that are involved in proactive delay measurement and how SDN can facilitate adaptability of the measurements to varying conditions.
Instrumenting Open vSwitch with Monitoring Capabilities: Designs and ChallengesAJAY KHARAT
With the advancement of SDN and NFV techniques a series of work was proposed:
OpenSketch, DREAM, FlowRadar, Trumpet
Hybrid solution that balances the tradeoff between FCAP (higher accuracy) and SMON (less memory)
Alternative data structure to Ring Buffer that would consume less memory
Achieve a design of integration that has the minimal forwarding-monitoring function interference, optimal code sharing and efficient CPU/Memory resource usage
NS4: Enabling Programmable Data Plane SimulationAJAY KHARAT
Programmable data plane with multiple devices can now be simulated
Simulation setup much easier compared to ns-3
Direct migration of simulated behaviour to real-world devices possible
Less error prone code writing.
Performance improved significantly.
Relevance of YATES
Representing real life scenarios
Capturing the actual impact of factors in the simulation
Runtime Parameters
Number of rules
Failure Model
Predicting new Traffic Matrix
Life in the Fast Lane: A Line-Rate Linear RoadAJAY KHARAT
Network hardware was simple and fixed.
Cannot change the underlying code.
As new generation of programmable switches which match the performance of fixed function devices has become commercially available
like consensus protocols, in-network caching etc..
One common feature of all these applications is that they depend on stateful computations.
If this trend continues—as appears likely—then it is worth identifying which abstractions are needed to support a more general form of stateful processing. How?
How to implement complex policies on existing network infrastructure AJAY KHARAT
Network has grown complex today and requires several features like VPN, firewall, intrusion detection etc
Network wide policy cannot be defined on a single switch(approximately around 750 entries per table), requires too much memory and computation
Need to split policy into several switches
Network-Wide Heavy-Hitter Detection with Commodity SwitchesAJAY KHARAT
Network operators often need to identify outliers in network traffic, to detect attacks or diagnose performance problems.
In order to detect such problems network operators perform heavy hitter detection for flows.
In the traditional system, the heavy hitter detection was done using analysing packets or examining the packet flows.
Prior work was focus on detecting heavy hitters on a single switch but we often need to track network-wide heavy hitters.
While detecting heavy hitters on network wide basis we will try to reduce the communication overhead while maintaining the accuracy.
p4pktgen: Automated Test Case Generation for P4 ProgramsAJAY KHARAT
Traditional network devices - fixed set of capabilities
Rise of programmable network devices in recent years
Offers great flexibility / capability than traditional network devices
Flexibility introduces new bugs:
Hardware
Toolchains
Programs
These bugs were previously covered by traditional network devices due to fixed set of capabilities
Use test cases to check whether program is behaving as intended on the device
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
3. Problem statement
A function-based dataplane, despite its advantages, faces two key challenges in
supporting multi-tenancy:
• Memory isolation
• Performance isolation
4. Approach And Solution
How performance isolation is achieved through FastPass?
• Multiple process from multiple tenants comes to FastPass
• FastPass controller configures NIC to decide upon resource management and
scheduling decision.
• It uses round-robin scheduling
• In FastPass , processing cost varies depending upon nature and path taken by a
packet, thus it provides fairness to tenants
• FastPaas tracks the CPU consumption of each tenant.
• FastPass contains primitives to calculate the processing cost of individual modules
as well as for a service chain
• NIC controller able to control scheduling of NF’s hence fairness is achieved , initially
it was done by OS which was difficult to manage
6. How Memory Protection is achieved through FastPass?
3 approaches to memory protection are as follows:
• Memory safe language: Writing modules in memory safe language like Rust
automatically manages memory but already there are NF’s written in C/C++ ,
rewriting them from scratch with Rust will takes lots of effort.
• Hardware-based memory protection(fine-grained approach): overhead of MPX
comes from loading/storing the individual bounds for every pointers in a program
• Coarse-grained hardware protection: Divides memory space into modules based on
tenancy , having 2 advantages:
• Tenants cant access each other modules and reduces the size of bound table thus
reducing lookup overhead.
7.
8. Evaluation of the solution
• We evaluate two NFs with different processing costs per packet
1. macswap(less costly)
2. traffic policer (more costly)
• FastPaas/RW achieve a throughput of 86% for macswap and 82% for the traffic policer compared to
the unprotected module.
• FastPaas/WOnly acheives an even higher throughput of 96% and 98% of the unprotected module.
1.Macswap Preallocated pkts Policer Preallocated pkts Policer real pkts
9. Related Work
SafeCode provides memory isolation using a combination of static
analysis and minimal runtime but it is unable to protect packets
declared by DPDK in our tests.
FastPass fairly distribute CPU resources but it does not balance the
CPU usage across cores so we use FlexNIC below FastPass which
automatically compute the load balancing filters based on packet
processing graph specifications and traffic measurements.
10. Future Work
• The weight of a queue is statically defined based on the priority of a
tenant. Further study of scheduling strategies (including strict priority
classes) is ongoing.
• Comparing Rust with FastPaas for policer and other modules is a topic
of our ongoing work