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COMP9334 Computing clusters
创建日期：2024-08-13 15:19:57
标签： COMP9334
Computing clusters
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COMP9334
Computing clusters
Version 1.01
Updates to the project, including any corrections and clarifications, will be posted on the
course website. Make sure that you check the course website regularly for updates.
Change log
? Version 1.01 (27 March 2024). There is a mistake in the denominators of the two probability
density functions in Section 5.1.1. For g0(t), it should be t raised to the power of η0+1 where
the +1 was missing. A similar error appeared in g1(t), it should be t raised to the power of
η1+1.
? Version 1.00. Issued on 19 March 2024.
1 Introduction and learning objectives
You have learnt in Week 4A’s lecture that a high variability of inter-arrival times or service times
can cause a high response time. Measurements from real computer clusters have found that the
service times in these clusters have very high variability [1]. The reference paper [1] also has a
number of suggestions to deal with this issue. One suggestion is to separate the jobs according
to their service time requirements, and have one set of servers processing jobs with short service
times and another set of servers for jobs with long service times. This arrangement is the same
as supermarkets having express checkouts for customers buying not more than a certain number
of items and other checkouts that do not have a limit on the number of items. You had seen this
theory in action in Week 4A’s revision Problem 1. We also highly recommend you to read the
paper [1].
In this project, you will use simulation to study how to reduce the response time of a server
farm that uses different servers to process jobs with different service time requirements.
In this project, you will learn:
1. To use discrete event simulation to simulate a computer system
2. To use simulation to solve a design problem
3. To use statistically sound methods to analyse simulation outputs
We mentioned a number of times in the lectures that simulation is not simply about writing
simulation programs. While it is important to get your simulation code correct, it is also important
that you use statistically sound methods to analyse simulation outputs. There, roughly half of
the marks of this project is allocated to the simulation program, and the other half to statistical
analysis; see Section 7.2.
1
Server 0
Server n - 1
New jobs
submitted
by users
Dispatcher
?
?
?
Queue 0 ↓
Queue 1 ↑
Jobs that have completed
their processing will
depart the system
permanently
Jobs that are killed are
sent back
to the dispatcher
Jobs killed by servers in
Group 0
Server n0
Server n0 - 1
?
?
?
Jobs that have completed
their processing will
depart the system
permanently
Group 0 →
Group 1 →
Figure 1: The multi-server system for this project.
2 Support provided and computing resources
If you have problems doing this project, you can post your question on the course forum. We
strongly encourage you to do this as asking questions and trying to answer them is a
great way to learn. Do not be afraid that your question may appear to be silly, the
other students may very well have the same question! Please note that if your forum post
shows part of your solution or code, you must mark that forum post private.
Another way to get help is to attend a consultation (see the Timetable section of the course
website for dates and times).
If you need computing resources to run your simulation program, you can do it on the VLAB
remote computing facility provided by the School. Information on VLAB is available here: https:
//taggi.cse.unsw.edu.au/Vlab/
3 Multi-server system configuration with job isolation
The configuration of the multi-server system that you will use in this project is shown in Figure
1. The system consists of a dispatcher and n servers where n ≥ 2. The n servers are partitioned into 2 disjoint groups, called Groups 0 and 1, with at least one server in each group. The
number of servers in Groups 0 and 1 are, respectively, n0 and n1 where n0, n1 ≥ 1 and n0+n1 = n.
The servers in Group 0 are used to process short jobs which require a processing time of no
more than a time limit of Tlimit. The servers in Group 1 do not impose any limit on service time.
2
The dispatcher has two queues: Queue 0 and Queue 1. The jobs in Queue i (where i = 0, 1)
are destined for servers in Group i. Both queues have infinite queueing spaces.
When a user submits a job to this multi-server system, the user needs to indicate whether the
job is intended for the servers in Group 0 or Group 1. The following general processing steps are
common to all incoming jobs:
? If a job is intended for a server in Group i (where i = 0, 1) arrives at the dispatcher, the job
will be sent to a server in Group i if one is available, otherwise the job will join Queue i.
? When a job departs from a server in Group i, the server will check whether there is a job at
the head of Queue i. If yes, the job will be admitted to the available server for processing.
Recall that the servers in Group 0 have a service time limit. The intention is that the users
make an estimate of the service time requirement of their submitted jobs. If a user thinks that
their job should be able to complete within Tlimit, then they submit it to Group 0; otherwise, they
should send it to the Group 1.
Unfortunately, the service time estimated by the users is not always correct. It is possible that
a user sends a job which cannot be completed within the time limit to Group 0. We will now
explain how the multi-server system will process such a job. Since the user has indicated that the
job is destined for Group 0, the job will be processed according to the general processing steps
explained earlier. This means the job will receive processing by a server in Group 0. After this
job has been processed for a time of Tlimit, the server says that the service time limit is up and
will kill the job. The server will send the job to the dispatcher and tell it that this is a killed job.
The dispatcher will check whether a server in Group 1 is available. If yes, the job will be send to
an available server; otherwise, it will join Queue 1 to wait for a server to become available. When
a server in Group 1 is available to work on this job, it will process the job from the beginning,
i.e., all the previous processing in a Group 0 server is lost.
If a job has completed its processing at a Group 0 server, which means its service time is less
than or equal to Tlimit, then the job leaves the multi-server system permanently. Similarly, a job
completed its processing at a Group 1 server will leave the system permanently.
We make the following assumptions on the multi-server system in Figure 1. First, it takes
the dispatcher negligible time to classify a job and to send a job to an available server. Second,
it takes a negligible time for a server to send a killed job to the dispatcher. Third, it takes a
negligible time for a server to inform the dispatcher on its availability. As a consequence of these
assumptions, it means that: (1) If a job arriving at the dispatcher is to be sent to an available
server right away, then its arrival time at the dispatcher is the same as its arrival time at the
chosen server; (2) The departure time of a job from the dispatcher is the same as its arrival time
at the chosen server; and (3) The departure time of a killed job from a server is the same as its
arrival time at the dispatcher. Ultimately, these assumptions imply that the response time of the
system depends only on the queues and the servers.
We have now completed our description of the operation of the system in Figure 1. We will
provide a number of numerical examples to further explain its operation in Section 4.
You will see from the numerical examples in Section 4 that the number of Group 0 servers n0
can be used to influence the mean response time. So, a design problem that you will consider in
this project is to determine the value of n0 to minimise the mean response time.
Remark 1 Some elements in the above description are realistic but some are not. Typically,
users are required to specify a walltime as a service time limit when they submit their jobs to a
computing cluster. If a server has already spent the specified walltime on the job, then the server
3
will kill the job. All these are realistic.
The re-circulation of a killed job is normally not done. A user will typically have to resubmit
a new job if it has been killed. If a killed job is re-circulated, then it may be given a lower priority,
rather than joining the main queue which is the case here.
Some programming technique (e.g., checkpointing) allows a killed job or crashed job to resurrect from the last state saved rather than from the beginning. However, that may require a sizeable
memory space.
In order to make this project more do-able, we have simplified many of the settings. For
example, we do not use lower priority for the re-circulated killed jobs.
4 Examples
We will now present three examples to illustrate the operation of the system that you will simulate
in this project. In all these examples, we assume that the system is initially empty.
4.1 Example 0: n = 3, n0 = 1, n1 = 2 and Tlimit = 3
In this example, we assume the there are n = 3 servers in the farm with 1 (= n0) server in Group
0 and 2 (= n1) servers in Group 1. The time limit for Group 0 processing is Tlimit = 3.
Table 1 shows the attributes of the 8 jobs that we will use in this example. Each job is given
an index (from 0 to 7). For each job, Table 1 shows its arrival time, service time and the server
group that the user has indicated. For example, Job 1 arrives at time 10, requires 4 units of time
for service and the user has indicated that this job needs to go to a Group 0 server. Since the
service time requirement for this job exceeds the time limit Tlimit of 3, this job will be killed after
3 time units of service and will be sent to dispatcher after that.
Note that, a job which a user sends to a Group 0 server will be completed if its service time
is less than or equal to the service time limit Tlimit being imposed. So, Job 6 in Table 1 will be
completed in a Group 0 server and this job will not be killed.
Job index Arrival time Service time required Server group indicated
0 2 5 1
1 10 4 0
2 11 9 0
3 12 2 0
4 14 8 1
5 15 5 0
6 19 3 0
7 20 6 1
Table 1: Jobs for Example 0.
Remark 2 We remark that the job indices are not necessary for carrying out the discrete event
simulation. We have included the job index to make it easier to refer to a job in our description
below.
The events in the system in Figure 1 are
? The arrival of a new job to the dispatcher; and,
4
? The departure of a job from a server.
We remark that for a Group 1 server, a departed job has its service completed. However, for
a Group 0 server, a departed job can be a killed job or a completed job. Note that we have not
included the arrival of a re-circulated killed job to the dispatcher as an event. This is because the
arrival of a re-circulated job at the dispatcher is at the same time as the departure of that job
from a Group 0 server. So the simulation will handle these events together: the departure of a
killed job and its handling by the dispatcher.
We will illustrate the simulation of the system in Figure 1 using “on-paper simulation”. The
quantities that you need to keep track of include:
? Next arrival time is the time that the next new job (i.e, not a killed job) will arrive
? For each server, we keep track its server status, which can be busy or idle.
? We also keep track of the following information on the job that is being processed in the
server:
– Next departure time is the time at which the job will depart from the server. If the
server is idle, the next departure time is set to ∞. Note that there is a next departure
time for each server.
– The time that this job arrived at the system. This is needed for calculating the response
time of the job when it permanently departs from the system.
? The contents of Queues 0 and 1. Each job in the queue is identified by a 2-tuple of (arrival
time, service time).
There are other additional quantities that you will need to keep track of and they will be
mentioned later on.
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MAS316/414 ACCT2522 MSIN0181 ATMS 201 COMP3425 MATH7861 SOLA2060 MA 325 7CCEMCTH ECON 432 INFT2051 SOLA 2060 ECOS2002 Stats141XP BIOA02H3 S2022 MA4601 K5 COMP5329 EG 284 IB3A70 WECO1020 COMP3027 Energy ACS61011 MAST20026 STAT 533 MATA31 ENVS257 BEM2031 EC 486 COMP0172 CS3214 EECE5644 IB2B20 COSC2536 COSC1147 COMP6214 5CCM242A COMP0130 AMME2000 MTMG50: EG238 ACF6006 QBUS2810 COSC2391 ECON7560 MATH377 STA305 CS 486 COMP1117B EL648 ELEC3909 ECON 241 COMP 4901W BUSI4428 ENEN20002 ENGN4524 ELEC3115 CSC 413 PSYC 100B ECON1002 MATH256 ANSC20005 MTHS2008 MATH40082 COSC 2406 FIT3174 STA 238 CMT202 Differential Equations MTHM017 GARCH 101 MATH2069 CSC336S ACSC12 ETF2121 CEME 2001 DB B474F ARHT1001 EECS 3311 3220 STATS 786 CS 484 COMP20008 MATH4091 ECE 455 CSCI 204 BUS B200F BA 875 BU5562 COSC 1147 X11 GEOG 101 IMM250F CSE 584A MATH38172 LAB 4 ELEC5882M FINS5523 EE 430 COMP 465 6CCS3PRE 7CCSMNSE FINANCE ACMB02H3 ENGG2112 ELEC5616 SCM B371 CHEM3120 CS22 ECMT2130 MAST30011 ADSPBF706 CENG0013 ACCOUNTING BUSS1040 CHEM 181 MAT136H1 GY 6183 COMP3170 AGRI90089 PHYSICS 1002 ECON10003 IEOR E4004 ACS61012 MATH 40550 MKTG2113 TELE4653 ENSC1004 ECE 232E MK726 MTRX2700 SHEET 3 CSCA08 COMP30027 Math 2XX3 statistic MMAN3200 BISM7213 ECMM109 ECON 2022 FNCE 20005 GR5067 CSCB09 ME 3017 CS 5100 PHYS 2903 COMS 4771 COMP222 COMP 1046 CSC148H1 ISYS2038 FINS2615 OT5206 COMP2048 A6 MECH5770M MA826/20 CMPT 726 STA457 INFS6071 INFS588 integral ECON 216 IRDR 0017 MA323 PA 15213 PSYC2001 ENV222 Statistics ACCT5930 ACCT12 LAND2121 ME 5405 COMM1180 TELE3113 A7 ECE 568 ACCT2019 INFS1200 ENGG1340 CS 1400 ASST3 FINM7409 SWEN30006 INFO2222 FIN20150 SOSS1000 CSSE7231 FINS5513 COMS3200 CECN 702 ECON4060H MN3515 HW2 PSYA02H3 ECON 2112 COMP90051 CS 1652 MA30059 AF1605 MKTG7501 ECO-6003B COM4521 CTM ECON3350 COMP 3804 ELEC9762 BISM 7255 ST22 MATH20014 MNE3122 COMP343 MATH5165 ELE7029 ENGR30002 SEEM3500 ECON7350 RISK5002 FINM7405 COMP90059 MOS 3320B STAT 431 BISM7221 MATH3014 MTH783P EBA 35302 ACS133 BUS2206 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