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.
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.
Exploiting latency bounds for energy efficient load balancingMichael May
These slides are taken from a research paper the PSL group wrote while under the direction of Dr. Vijay Garg at the Universtiy of Texas at Austin. The abstract is provided below.
In this paper we explore exploitation of latency bounds in order to gain energy efficiency in load balancing applications. We are proposing an energy aware job scheduler that uses vary-on, vary-off features in order to maximize time spent at peak utilization, while maintaining bounded latency. Computing resources will either be at load saturation(highest work per joule) or off. The premise being that servers are most efficient at peak utilization, measured in terms of energy per calculation. We explore the efficiency gains achieved through this approach and compare our results to other methods.
Instruction Level Parallelism and Superscalar ProcessorsSyed Zaid Irshad
Common instructions (arithmetic, load/store, conditional branch) can be initiated and executed independently
Equally applicable to RISC & CISC
In practice usually RISC
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.
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.
Exploiting latency bounds for energy efficient load balancingMichael May
These slides are taken from a research paper the PSL group wrote while under the direction of Dr. Vijay Garg at the Universtiy of Texas at Austin. The abstract is provided below.
In this paper we explore exploitation of latency bounds in order to gain energy efficiency in load balancing applications. We are proposing an energy aware job scheduler that uses vary-on, vary-off features in order to maximize time spent at peak utilization, while maintaining bounded latency. Computing resources will either be at load saturation(highest work per joule) or off. The premise being that servers are most efficient at peak utilization, measured in terms of energy per calculation. We explore the efficiency gains achieved through this approach and compare our results to other methods.
Instruction Level Parallelism and Superscalar ProcessorsSyed Zaid Irshad
Common instructions (arithmetic, load/store, conditional branch) can be initiated and executed independently
Equally applicable to RISC & CISC
In practice usually RISC
We present a Ternary Content-addressable Memory (TCAM) design which is based on the use of floating-gate (flash) transistors.
TCAMs are extensively used in high speed IP networking, and are commonly found in routers in the internet core. Traditional TCAM ICs are built using CMOS devices, and a single TCAM cell utilizes 17 transistors. In contrast, our TCAM cell utilizes only 2 flash transistors, thereby significantly reducing circuit area.
We are focusing mainly on the TCAM block which does fast parallel IP routing table lookup. Our flash-based TCAM (FTCAM) block is simulated in SPICE, and we show that it has a significantly lowered area compared to a CMOS based TCAM block, with a speed that can meet current (400 Gb/s) data rates that are found in the internet core.
Client-Centric Consistency
Provide guarantees about ordering of operations only for a single client, i.e.
Effects of an operations depend on the client performing it
Effects also depend on the history of client’s operations
Applied only when requested by the client
No guarantees concerning concurrent accesses by different clients
Assumption:
Clients can access different replicas, e.g. mobile users
checking dependencies between instructions to determine which instructions can be grouped together for parallel execution;
assigning instructions to the functional units on the hardware;
determining when instructions are initiated placed together into a single word.
Optimization of Electrical Machines in the Cloud with SyMSpace by LCMcloudSME
Presented at NAFEMS DACH regional conference for numerical simulation methods by LCM and cloudSME in Wiesbaden on the 14th of November 2019.
The Linz Center of Mechatronics GmbH showcased how they easily optimize electrical drive engines in the cloud.
We supported LCM to work out the right cloud-based service solutions for their customers based on their existing software. By respecting the latest developments in the industry and science, including security and privacy compliance and hosting flexibility (free choice of data centre, no vendor lock-in).
Check out their cool System Model Space "SyMSpace" for electrical drive engines and trusted by industrial partners! (https://bit.ly/2CKGphb) #poweredbycloudSME
Yes, Cloud Computing is offering a broad range of actions and can be confusing. You want to dig deeper?
Write us an email or give us a call so that we can work out how to approach the perfect cloud solution for your needs.
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
We present a Ternary Content-addressable Memory (TCAM) design which is based on the use of floating-gate (flash) transistors.
TCAMs are extensively used in high speed IP networking, and are commonly found in routers in the internet core. Traditional TCAM ICs are built using CMOS devices, and a single TCAM cell utilizes 17 transistors. In contrast, our TCAM cell utilizes only 2 flash transistors, thereby significantly reducing circuit area.
We are focusing mainly on the TCAM block which does fast parallel IP routing table lookup. Our flash-based TCAM (FTCAM) block is simulated in SPICE, and we show that it has a significantly lowered area compared to a CMOS based TCAM block, with a speed that can meet current (400 Gb/s) data rates that are found in the internet core.
Client-Centric Consistency
Provide guarantees about ordering of operations only for a single client, i.e.
Effects of an operations depend on the client performing it
Effects also depend on the history of client’s operations
Applied only when requested by the client
No guarantees concerning concurrent accesses by different clients
Assumption:
Clients can access different replicas, e.g. mobile users
checking dependencies between instructions to determine which instructions can be grouped together for parallel execution;
assigning instructions to the functional units on the hardware;
determining when instructions are initiated placed together into a single word.
Optimization of Electrical Machines in the Cloud with SyMSpace by LCMcloudSME
Presented at NAFEMS DACH regional conference for numerical simulation methods by LCM and cloudSME in Wiesbaden on the 14th of November 2019.
The Linz Center of Mechatronics GmbH showcased how they easily optimize electrical drive engines in the cloud.
We supported LCM to work out the right cloud-based service solutions for their customers based on their existing software. By respecting the latest developments in the industry and science, including security and privacy compliance and hosting flexibility (free choice of data centre, no vendor lock-in).
Check out their cool System Model Space "SyMSpace" for electrical drive engines and trusted by industrial partners! (https://bit.ly/2CKGphb) #poweredbycloudSME
Yes, Cloud Computing is offering a broad range of actions and can be confusing. You want to dig deeper?
Write us an email or give us a call so that we can work out how to approach the perfect cloud solution for your needs.
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
Implementing True Zero Cycle Branching in Scalar and Superscalar Pipelined Pr...IDES Editor
In this paper, we have proposed a novel architectural
technique which can be used to boost performance of modern
day processors. It is especially useful in certain code constructs
like small loops and try-catch blocks. The technique is aimed
at improving performance by reducing the number of
instructions that need to enter the pipeline itself. We also
demonstrate its working in a scalar pipelined soft-core
processor developed by us. Lastly, we present how a superscalar
microprocessor can take advantage of this technique and
increase its performance.
Faster microprocessor design presentation in American International University-Bangladesh (AIUB). Presentation was taken under the subject "SELECTED TOPICS IN ELECTRICAL AND ELECTRONIC ENGINEERING (PROCESSOR AND DSP HARDWARE DESIGN WITH SYSTEM VERILOG, VHDL AND FPGAS) [MEEE]", as a final semester student of M.Sc at AIUB.
Pipelining is an implementation technique where multiple instructions are overlapped in execution. The computer pipeline is divided in stages. Each stage completes a part of an instruction in parallel.
Concurrent Replication of Parallel and Distributed SimulationsGabriele D'Angelo
Parallel and distributed simulations enable the analysis of complex systems by concurrently exploiting the aggregate computation power and memory of clusters of execution units. In this work we investigate a new direction for increasing both the speedup of a simulation process and the utilization of computation and communication resources. Many simulation-based investigations require to collect independent observations for a correct and significant statistical analysis of results. The execution of many independent parallel or distributed simulation runs may suffer the speedup reduction due to rollbacks under the optimistic approach, and due to idle CPU times originated by synchronization and communication bottlenecks under the conservative approach. We present a parallel and distributed simulation framework supporting concurrent replication of parallel and distributed simulations (CR-PADS), as an alternative to the execution of a linear sequence of multiple parallel or distributed simulation runs. Results obtained from tests executed under variable scenarios show that speedup and resource utilization gains could be obtained by adopting the proposed replication approach in addition to the pure parallel and distributed simulation.
An Introduction to TensorFlow architectureMani Goswami
Introduces you to the internals of TensorFlow and deep dives into distributed version of TensorFlow. Refer to https://github.com/manigoswami/tensorflow-examples for examples.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Lecture2
1. CS-416 Parallel and Distributed Systems JawwadShamsi Lecture #2 19th January 2010
2. How Much of Parallelism Decomposition: The process of partitioning a computer program into independent pieces that can be run simultaneously (in parallel). Data Parallelism Task Parallelism
3. Scalar Instruction Single Instruction at a time Load R1 @ 1000 Vector Instruction Vector operations C(1:100)=A(1:100)+B(1:100) Super computer Vector Instructions with pipelined floating point arithematic
4. Pipelining Pipelining overlaps various stages of instruction execution to achieve performance. At a high level of abstraction, an instruction can be executed while the next one is being decoded and the next one is being fetched. This is akin to an assembly line for manufacture of cars.
5. Pipeline-limitations Pipelining, however, has several limitations. The speed of a pipeline is eventually limited by the slowest stage. For this reason, conventional processors rely on very deep pipelines (20 stage pipelines in state-of-the-art Pentium processors). However, in typical program traces, every 5-6th instruction is a conditional jump! This requires very accurate branch prediction. The penalty of a misprediction grows with the depth of the pipeline, since a larger number of instructions will have to be flushed.
6. Pipelining and Superscalar Execution One simple way of alleviating these bottlenecks is to use multiple pipelines. The question then becomes one of selecting these instructions.
7. Super Scalar Execution Issue multiple instructions during the same CPU cycle How? By simultaneously dispatching multiple instructions to redundant units not a separate CPU core but an execution resource within a single CPU e.g. ALU
