scheduling in next generation os

Scheduling in Next Generation Operating Systems

Presented By:

Santosh G. Nage

Guide:

Prof. Girish Potdar

HOD (Computer Engineering)

April 24, 20141

o Need

o Motivation

o Literature Survey

o Objective

o Architecture of multi-core processor

o Scheduler design

o New scheduling policy

o Proposed MM

o Implementation

o Advantages

o Conclusion

o References

Agenda

Scheduling in Next Generation Operating Systems 2

Need

Scheduling in Next Generation Operating Systems3

…

Moore’s Law for Software??

…

Moore’s law

speed of computers doubled every 18-24 months

Need

Scheduling in Next Generation Operating Systems4

o Scheduling - directly affects the performance of the system.

o The existing scheduler does not necessarily yield the best

performance for multi-core systems.

o Need - new scheduling policy specifically for multi-core

systems.

Motivation


o Existing Scheduling policies are not optimally utilizing CPU resources.

o To modify the existing scheduling policy for multi-core systems.

o To solve a given problem with different performances under different

circumstances. We need to specify several algorithms for each task

and OS selects the most suitable one.

o Breaking tasks among several cores to implement parallel working.

Literature Survey

Name of paper Name of Author Key idea

Cache Friendliness-Aware Management of Shared Last-Level Caches for High Performance Multi-Core Systems

Dimitris Kaseridis, Muhammad Faisal Iqbal, Lizy Kurian John

Last Level Cache management

Adaptive Cache Aware BitierWork-Stealing in Multi socket Multi core Architectures

Quan Chen, Minyi Guo, Zhiyi Huang

Traditional approach with divide and conquer

On benefits of Work Stealing in Shared Memory Multiprocessors

Danial Neill, Adam Wierman Stealing is better than sharing

6Scheduling in Next Generation Operating Systems

Objectives


o To study existing Different Scheduling Policies.

o To understand the data structures and functions.

o To design new scheduling policy, which will give better performance

on the Multi-core machines as compared to existing policy.

o To embed the newly implemented policy into existing scheduler.

o Compare the performance on multi-core system.

Architecture of Multi-core


Scheduler Architecture


Sched_mcoreSched_fair (CFS) Sched_rt

SCHEDULER

SCHED_FIFOSCHED_RRSched_mcoreSCHED_NORMAL SCHED_NORMAL

Task of scheduler

• Be fair – give each process a fair share of the CPU, allow each process to run in a reasonable amount of time.

• Be efficient – keep the CPU busy all the time.

• Maximize throughput – service the largest possible number of jobs in a given amount of time; minimize the amount of time users must wait for their results.

• Minimize response time – interactive users should see good performance.

• Be predictable – a given job should take about the same amount of time to run when run multiple times.

• Minimize overhead – don’t waste too many resources. Keep scheduling time and context switch time at a minimum.

• Maximize resource use – favour processes that will use underutilized resources. Giving the process more CPU time may free up the resource quicker.

• Enforce priorities – if the scheduler allows a process to be assigned a priority, it should be meaningful and enforced.


New Scheduling Policy

• Work Sharing

A working core with parallel task queries see the other which is free to take on additional work.

• Work Stealing

A core that finds itself without work simply selects one other core at random and pulls task out of its queue.

• Work shrugging

Pushing surplus work away from busy processors onto less loaded neighbours, rather than have idle processors pulling work from busy neighbours


Proposed Mathematical Model

Let, S:Y= fs (X) be a system such that

S = {s,e,X,Y,Ep,Sp,Cp,DD,NDD,Sr,F }

s-be start state of the system

e-be end state of the system

X-be the set of processes as set of input to the multi-core processor .

{ P1,P2,P3,…..}

Sr-be the shared resources.

{Sr1,Sr2,Sr3,…..}

Ep-set of execution times of processes.

{ep1,ep2,ep3,…..}

Sp-set of spawned process.

{sp1,sp2,sp3…..}


NDD- A given multithreaded program when run on a given input can sometimes generate more than one multithreaded computation.

DD- The same multithreaded computation is generated by the program on the input no matter how the computation is scheduled, then the program is deterministic.

Tcp-set of tasks scheduled on cores of processor.

Total time required for execution is

Tcp= min(Epi) where i=1,2,3…..

one core can execute only one instruction at a time.

T∞-critical path as many instructions per core.

We must have,

Tcp≥T1/(P+T∞)


Tcp≥T∞

T there exist P -processor execution schedules X with

T(X ) ≤ T1=P + T1.

Consider the execution of any multithreaded computation with critical path length ‘T∞’ by scheduling algo. On parallel computer with Cp-multi-core processor.

for any € > 0 probability at least (1-€). At most

O(P(T∞+log(1/€))) work stealing occurs.

Each process allocates a task on each core.

F(allocate): P Cp

If Cp is ideal then it steals an instruction of randomly a core.

F(rand) : P(Sp1,Sp2,Sp3…..)Cp


It returns back the results to the victim core.

F(return) :Cp(Y)P

Y-tasks are scheduled on the cores and gives output.


Implementation


o Steps involved in the implementation:

o Install Linux (Ubuntu 12.04 LTS) 64-bit

o Download Linux source code 3.14.1

o Analyze dependencies of sched.c and kernel source

o Implementing new scheduling policy

o Embed new scheduling policy into existing scheduler

o Make necessary changes in other files

Advantages


• Scalable performance in accordance cores with minimal

communication overhead.

• Scheduling can support core-affinity.

• Simple approach to avoid code complexity.

• Maintainable as code available as a patch.

• Improved performance because of optimal core utilization.

• Improved flexibility in the design.

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Conclusion

o In this seminar, the existing scheduler has been modified

for the multi-core systems.

o A new scheduling policy has been designed and

implementing specifically for the multi-core systems.

o In future different scheduling policies and the criteria's for

multi-core processor will be coined and designed for

maximizing the CPU resources more efficiently.

o Concept of Hyper Threading Technology can be introduced.


References


[1] A. Silberschatz, P.B. Gailvin, G. Gagne, “Operating System Concepts,” 7th Edition, John Wiley

& Sons Inc., 2005.

[2] Yizhuo Wang, Weixing Ji, Qi Zuo, Feng Shi, “A Hierarchical Work-Stealing Framework for

Multi-core Clusters”, 2012 13th International Conference on Parallel and Distributed Computing,

Applications and Technologies

[3 Javier Diaz, Camelia Mun˜oz-Caro, and Alfonso Nino, " A Survey of Parallel Programming Models and Tools in the Multi and Many-Core Era,” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 23, NO. 8, AUGUST 2012.

[4 Dimitris Kaseridis, Muhammad Faisal Iqbal, Lizy Kurian John, Cache Friendliness-Aware Management of Shared Last-Level Caches for High Performance Multi-Core Systems," IEEE TRANSACTIONS ON COMPUTERS, VOL. 63, NO. 4, APRIL 2014.

[5 James Dinan, D. Brian Larkins,P. Sadayappan, Sriram Krishnamoorthy, Jarek Nieplocha" Scalable Work Stealing,” SC 09 November 14-20, 2009, Portland, Oregon, USA Copyright 2009 ACM 978-1-60558-744-8/09/11

[6 ]R.M. Ramanathan , Intel® Multi-Core Processors Making the Move to Quad-Core and Beyond,” White Paper.

[7] SIMON PETER," Resource Management in a Multicore Operating System “, PhD thesis in 2012

[8] Quan Chen, Minyi Guo, Zhiyi Huang “Adaptive Cache Aware Bitier Work-Stealing in Multisocket Multicore Architectures” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24 NO 12, DEC 2013

[ 9 ] Danial Neill, Adam Wierman, “On benefits of Work Stealing in Shared Memory Multiprocessors” .

[ 10 ] Shay Gal-On and Markus Levy, “Measuring Multi-core Performance”, Published by IEEE Computer Society Nov 2008.

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References
