Aalto University School of Electrical Engineering Department of Signal Processing and Acoustics Michele Lindroos Task Scheduling in Conversational Multicore Speech Processing Systems Master's Thesis Espoo, September 1, 2014 Supervisor: Prof. Paavo Alku Instructor: Joakim Haldin M.Sc. Aalto University School of Electrical Engineering ABSTRACT OF Department of Signal Processing and Acoustics MASTER'S THESIS Author: Michele Lindroos Title: Task Scheduling in Conversational Multicore Speech Processing Systems Date: September 1, 2014 Pages: 60 Professorship: Speech Communication Technology Code: S-89 Supervisor: Prof. Paavo Alku Instructor: Joakim Haldin M.Sc. The perceptual speech quality of conversational speech, such as in mobile phone calls, degrades with mouth-to-ear delay and packet loss. Some calls need their speech packets to be altered, for example because of transcoding. If these calls run concurrently and share the same computational resources, it's important that the resource division works so that the mouth-to-end delay and packet loss is minimized. Such division of the resources is commonly called scheduling. In this work multiple scheduling algorithms are reviewed and tested using a pro- totype network. The dierent schedulers are analyzed by looking at the jitter and packet loss they achieve. Also multicore scheduling is taken into account in this work. The results show that for simple trac models used in this work, simple algo- rithms are very ecient. Furthermore, the results align well with the theoretical analysis of the schedulers. An important nding is also that scheduler character- istics do not change with the amount of processor cores used. Keywords: scheduling, real-time, speech coding, multicore Language: English 2 Aalto-yliopisto Sähkötekniikan korkeakoulu DIPLOMITYÖN Signaalinkäsittelyn ja akustiikan laitos TIIVISTELMÄ Tekijä: Michele Lindroos Työn nimi: Tehtäväajastus vuorovaikutteisissa moniytimisissä puheenkäsittelyjärjestelmissä Päiväys: 1. syyskuuta 2014 Sivumäärä: 60 Professuuri: Puhekommunikaatiotekniikka Koodi: S-89 Valvoja: Prof. Paavo Alku Ohjaaja: FM Joakim Haldin Havaitun puheen laatu heikkenee kokonaisviiveen ja pakettihäviöiden lisään- tyessä, mikäli kyseessä on keskusteluun käytettävä yhteys, kuten matkapuhelin- verkossa yleensä. Osa puheluista vaatii, että näiden puhepaketteja muutetaan lennossa verkossa, esim. transkoodauksen takia. Mikäli nämä puhelut ovat käyn- nissä yhtä aikaa ja ne jakavat samoja laskentaresursseja, täytyy nämä resurssit jakaa siten että kokonaisviive ja pakettihäviöt pysyvät minimissä. Tätä resurssien jakoa kutsutaan usein tehtäväajastamiseksi. Tässä työssä käydään läpi ja testataan useaa eri tehtäväajastusalgoritmia. Testit suoritetaan käyttäen prototyyppiverkkoa. Eri tehtäväajastimia analysoidaan kat- somalla minkälaisia viive-eroja ja pakettihäviöitä syntyy käyttämällä niitä. Myös moniytimisen järjestelmän tehtäväajastusta testataan. Tulokset osoittavat, että koska testeissä käytetään verrattain yksinkertaisia liiken- nemalleja, yksinkertaiset tehtäväajastusalgoritmit suoriutuvat tehtävästään hyvin tehokkaasti. Lisäksi, tulokset osoittavat teoreettisen analyysin paikkansapitävyy- den. Myös tulosten johdonmukaisuus moniytimisessä järjestelmässä on merkittävä löytö. Asiasanat: ajastus, reaaliaikaisuus, puheenkoodaus, moniytimiset jär- jestelmät Kieli: Englanti 3 Aalto-universitetet Högskolan for elektroteknik SAMMANDRAG AV Institutionen för signalbehandling och akustik DIPLOMARBETET Utfört av: Michele Lindroos Arbetets namn: Process tidsplanering i konversationella mångkärniga tal processerings system Datum: Den 1 september 2014 Sidantal: 60 Professur: Talkommunikationsteknik Kod: S-89 Övervakare: Prof. Paavo Alku Handledare: FM Joakim Haldin Perceptuella talkvaliteten försämras med fördröjning och förlust av paket i kon- versationella nätverk. En del samtal kräver att talpaketen ändras i realtid i nätver- ket, t.ex. på grund av transcodning. Ifall dessa samtal delar samtidigt på samma databehandlingsresurser måste fördelningen av resursserna fungera så att för- dröjningen och paketförlusten är minimal. Den här typen av resursfördelning kallas ofta tidsplanering. I detta arbete granskas och testas ere process tidsplanerare. För testande an- vänds ett prototyp nätverk. De olika process tidsplanerarna analyseras genom att titta på hurdan jitter och hurdana paketförluster de uppnår. Även tidsplanering för erkärniga system tas i beaktande. Resultaten visar att för de enkla trakmodellerna som andänds i detta arbete, är enkla algoritmer är mycket eektiva. Vidare visar resultaten att de ansluter väl med teoretiska analysen av algoritmerna. Ett märkvärdigt resultat är också att tidsplanerarnas egenskaper inte varierar med antalet processorkärnor som används. Nyckelord: tidsplanering, realtid, talkodning, mångkärniga system Språk: Engelska 4 Acknowledgements I wish to thank Ericsson for the opportunity to do this work. A big thanks goes also to all the people who have helped me doing this work; Antti Pakari- nen, Joakim Haldin, Juri Lelli, Jussi Judin, Jussi "Pupu" Pekonen, Miika- Petteri Matikainen and Paavo Alku. Jorvas, September 1, 2014 Michele Lindroos 5 Contents 1 Introduction 8 2 Background 9 2.1 Speech Codecs . .9 2.2 Speech Quality . 11 2.3 Computational Task . 12 2.4 Division of Hardware Resources . 13 2.5 Task Scheduling . 13 3 Scheduler Characterization 15 3.1 Scheduling Algorithm Characterization . 16 3.2 Multiprocessor Scheduling . 17 3.3 Virtual Runtime . 18 4 Task Characterization 21 4.1 The Periodic and Sporadic Task Models . 22 4.2 The Rate-Based Execution Model . 23 4.3 Pfair and Derivatives . 25 5 Scheduling Algorithms 30 5.1 Simplistic Algorithms . 30 5.2 Analysis-Based Algorithms . 31 5.2.1 Algorithm PF . 31 5.2.2 Algorithm PD . 33 5.2.3 Algorithm PD2 ...................... 35 5.3 Heuristic Algorithms . 35 5.3.1 Staircase Scheduler . 36 5.3.2 Rotating Staircase Deadline Scheduler . 37 5.3.3 Completely Fair Scheduler . 37 5.3.4 Brain Fuck Scheduler . 39 6 6 Measurements and Results 40 6.1 Measurement System . 40 6.2 Measured Algorithms . 44 6.3 Measured Cases . 45 6.3.1 Unicore vs Multicore Performance . 46 6.3.2 Codecs with Dierent Weights . 46 6.3.3 Codecs with Dierent Frame Time Lengths . 48 6.4 Further Research Ideas . 48 7 Conclusion 55 7 Chapter 1 Introduction Building up a packet switched communication network has many challenges of which one is the division of the network resources adequately among dier- ent network functions. In this thesis the scope is to look at a network element oering speech transcoding. Since dierent parties communicating with each other using the network might not use the same speech coding algorithms, a speech transcoder is required to enable communication. In this thesis the focus is on inspecting the division of the computational resources that the speech transcoding requires. Simple division of computational resources may not be suitable since speech packets have time restrictions to meet. Furthermore, in a circuit switched network all resources demanded from the network are reserved at the beginning of a communication request, but this is not the case in the packet switched network. The utilization of the resources in packet switched networks may change rapidly. Network elements have to be prepared for this by behaving predictably in the case of high load, or even overload. The scope of this thesis is to nd out how the behavior of a speech transcoder network element varies depending on which task scheduler is cho- sen. Here, every request for a transcoding is treated as an individual task competing for the resources the network element oers. This network ele- ment runs some operating system software which provides multitasking, i.e. seemingly concurrent processing of dierent tasks, by using a task scheduler. This work is arranged as follows; First background technology and ter- minology is covered. In Chapter 3 scheduler characterizations are presented and discussed. Chapter 4 presents and discusses task models in a similar fashion. In Chapter 5 various scheduling algorithms are described. Chapter 6 presents a measurement system, benchmarks schedulers and shows results. Chapter 7 concludes the work. 8 Chapter 2 Background In packet switched communication networks various resources have to be shared between dierent functions and users. Resources include at least radio access, link capacity and computational resources of the network nodes. In this work the resources of interest are the network nodes doing computational work, and more specically the network nodes doing speech transcoding. In this chapter speech codecs and some aspects inuencing perceived speech quality are presented. Furthermore, technical implementations of net- work nodes doing speech transcoding are discussed. The focus of this thesis is to look at how some main factors aecting speech quality change depending on which task scheduler is chosen to be used on the network nodes. 2.1 Speech Codecs In digital communication networks that oer audio services which are mainly used for speech, such as mobile phone networks, the audio signal is always compressed in order to save bandwidth. Furthermore, speech codecs are gen- erally dierent from audio codecs: speech coders typically take advantage of voice production modeling hence achieving eective compression rates whereas audio compression is mainly based on modeling of human sound perception. In [26] speech coding algorithms are divided into two categories: • Waveform approximating codecs. When using