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Queueing analysis for multi-core performance improvement: Two case studies Deng, J.D. and Purvis, M.K. Dept. of Information Science., Univ. of Otago, Dunedin Telecommunication Networks and Applications Conference, 2007. ATNAC 2007. Australasian 1 Outline Introduction Evaluation model ◦ Tandem queueing model for two case studies Two case studies ◦ Snort ◦ POISE Conclusion 2 Outline Introduction Evaluation model Two case studies Conclusions 3 Introduction Analysis of Multi-core performance ◦ Tandem system model for applications ◦ Queueing analysis ◦ Problem Given a tandem queueing model, and find the optimal number of cores, so that the total service time is minimal Case studies ◦ Snort and POISE ◦ Evaluation results is consistent with queueing analysis 4 Outline Introduction Evaluation model Two case studies Conclusions 5 Evaluation model Tandem queueing model ◦ Pipeline ◦ Applications Being able to parallelized into independent procedures Each procedure can be served by one or more cores 6 Evaluation model Terms definition ◦ ◦ ◦ ◦ λ : arrival/departure rate μi : service time ci : number of cores n : total number of procedures Burke’s Theorem ◦ When tandem in a steady state Arrival rate = departure rate for each procedure 7 Evaluation model Problem definition ◦ Given the arrival rate (λ), processing times μi and a total number of cores available, find the optimal choice of ci, so that the total time in system is minimal. 8 Evaluation model To solve the problem ◦ Using D/D/c model for each procedure ◦ Arrival rate/departure rate/number of services ◦ D is for deterministic (D = λ) 9 Evaluation model D/D/c model ◦ No queueing delay ◦ Consider only processing overhead ◦ Total processing time T ◦ Total number of cores , C for maximum number of cores 10 Evaluation model To find minimum T ◦ Lagrange multiplier By letting → => 11 Evaluation model Lagrange multiplier ◦ In mathematical optimization, the method of Lagrange multipliers (named after Joseph Louis Lagrange) provides a strategy for finding the maxima and minima of a function subject to constraints Maximize f (x, y ) subject to g(x, y) = c Λ (x, y, λ) = f (x, y ) + λ (g (x, y) – c ) maximum : partial derivatives of Λ are zero 12 Evaluation model Lemma ◦ Assign the numbers of servers to the subsystems in proportion to the square roots of their processing time, respectively This lemma can also work well in more generic systems with M/D/c subsystems 13 Outline Introduction Evaluation model Two case studies Conclusions 14 Two case studies - Snort Snort ◦ A free and open source Network Intrusion Prevention System (NIPS) and Network Intrusion Detection System (NIDS) 15 Two case studies - Snort Snort flow 16 Two case studies - Snort Measurement ◦ Packets injection 100,000 to 1 million ◦ Queueing discipline: FIFO ◦ Using three types of traffic Attack free, light attacks, heavy attacks 17 Two case studies - Snort Scenario 1 ◦ Without pipelining ◦ Packet distribution: round-robin ◦ Packet rate Light: 0.1 packets/μs Medium: 0.2 packets/μs Heavy: 0.4 packets/μs 18 Two case studies - Snort Evaluation of scenario 1 ◦ Performance curve 19 Two case studies - Snort Scenario 2 ◦ With pipelining ◦ Queueing model M/D/c for core group 1 M/D/1 for core group 2 ◦ 2~8 number of Cores ◦ Packet rate Light: 0.1 packets/μs Medium: 0.2 packets/μs Heavy: 0.4 packets/μs 2.31 μs 0.12 μs 0.16 μs 20 Two case studies - Snort Evaluation of scenario 2 ◦ Performance curve 21 Two case studies - Snort Conclusions ◦ Scheme 2 copes much better with heavy packet traffic ◦ Relevant queueing delay is significantly reduced to minimum with 3-4 cores ◦ The 4-core results shown in Fig. 6 are consistent with Lemma 1 3 cores for group1 and 1 core for group 2 22 Two case studies - POISE POISE ◦ An image retrieval and organization application 23 Two case studies - POISE Measurement ◦ 200 images ◦ 3.2GHz Pentium 4 single-core with 1GB RAM 24 Two case studies - POISE Scenario 0.097s 0.007s 0.036 s Assignment of number of cores ◦ 4-core as an example ◦ round to 3 ◦ Group 1 : group 2 = 3:1 25 Two case studies - POISE Evaluation in 8-core ◦ Markovian image arrival rate 20 images per second 5+3 has a minimal total processing time 26 Outline Introduction Evaluation model Two case studies Conclusions 27 Conclusions A simplified tandem queueing model is analyzed for two case studies Using queueing analysis to gain quantitative assessment The ideal proportion of core number distribution is worked out 28