Analytical models for performance and energy consumption evaluation - PowerPoint PPT Presentation

Analytical models for performance and energy consumption evaluation of storage devices Eric Borba Universidade Federal de Pernambuco (UFPE) erb@cin.ufpe.br October, 2020

Agenda Introduction Methodology Models Experimental results Conclusion and future works EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Context Methodology Motivation Models Goal Experimental Results Why GSPN? Conclusion Context Cloud computing (explosive growth of data – Big data) • 90% of all data in the world (2018-2020) -> 163ZB (2025) • Storage systems represent: • 25-35% of the Cloud computing costs 13% energy consumption in data centers 90% of a transaction execution time EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Context Methodology Motivation Models Goal Experimental Results Why GSPN? Conclusion Context HDDs causes higher latency due to mechanical • positioning in random access Low capacity, shorter lifetime, and cost of SSDs are • some obstacles Alternatively, hybrid (SSD+HDD) approaches have • been proposed EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Context Methodology Motivation Models Goal Experimental Results Why GSPN? Conclusion Motivation Aspects, such as performance and energy consumption, • must be balanced Few works rely on GSPN (generalized stochastic Petri nets) • and comprise both metrics Effective arrangement through optimized data-placement • policies EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Context Methodology Motivation Models Goal Experimental Results Why GSPN? Conclusion Goal ”Conceive stochastic models to estimate energy consumption and performance of storage systems” EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Context Methodology Motivation Models Goal Experimental Results Why GSPN? Conclusion Why GSPN? Synchronization, resource sharing, conflicts • Non-exponential activities and zero delays (logical control) • Alternative to Markov chains generation (simulation • techniques) Analysis of quantitative and qualitative properties • EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Methodology Methodology Design of Experiments Models Tools and environment setting Experimental Results Conclusion Methodology Analytical models • Measurement step: moment matching/validation • Factorial design (20 replications): screening experiment • Three experiments: SPC (storage performance council) • Metrics: IOPS (input/output per second)/energy • consumption, and price/IOPS EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Methodology Methodology Design of Experiments Models Tools and environment setting Experimental Results Conclusion Design of experiments Experiment I Screening approach Main factors and second-order interactions Experiment II Random access (4KB; 70%_write) Experiment III Sequential access (1MB; 50%_write) Experiment IV Mixed access (1MB; 50%_write; 80%_rnd) EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Methodology Methodology Design of Experiments Models Tools and environment setting Experimental Results Conclusion Tools and environment setting (measurement step) Tools Iometer (benchmark) Oscilloscopes Environment EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Single storage model Methodology Multiple storage model Models Experimental Results Conclusion Single storage model EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Single storage model Methodology Multiple storage model Models Experimental Results Conclusion Multiple storage model EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction MomentMatching/Validation Methodology Experiment I: screening Models Experiment II: random access Experimental Results Experiment III: sequential access Conclusion Experiment IV: mixed access Moment matching – phase type EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction MomentMatching/Validation Methodology Experiment I: screening Models Experiment II: random access Experimental Results Experiment III: sequential access Conclusion Experiment IV: mixed access Validation EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction MomentMatching/Validation Methodology Experiment I: screening Models Experiment II: random access Experimental Results Experiment III: sequential access Conclusion Experiment IV: mixed access Experiment I: screening EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction MomentMatching/Validation Methodology Experiment I: screening Models Experiment II: random access Experimental Results Experiment III: sequential access Conclusion Experiment IV: mixed access Experiment II: random access EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction MomentMatching/Validation Methodology Experiment I: screening Models Experiment II: random access Experimental Results Experiment III: sequential access Conclusion Experiment IV: mixed access Experiment III: sequential access EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction MomentMatching/Validation Methodology Experiment I: screening Models Experiment II: random access Experimental Results Experiment III: sequential access Conclusion Experiment IV: mixed access Experiment IV: mixed access EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Remarks Methodology Conclusion Models Future works Experimental Results Conclusion Remarks HDDs performance issues: small objects, random • access, simultaneous requests For sequential accesses, and large objects, HDDs • are still a feasible option SSDs: suitable for small random readings • Hybrid: for systems in which performance • requirements prevail over energy consumption EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Remarks Methodology Conclusion Models Future works Experimental Results Conclusion Conclusion An approach based on GSPN for assessment of • storages Evaluation of different technologies and workloads • Experiments illustrate the practical feasibility • EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Introduction Remarks Methodology Conclusion Models Future works Experimental Results Conclusion Future Works ”As future work, we are developing models for assessing the reliability and availability of storage systems” EricBorba (erb@cin.ufpe.br) Analytical models for performance and energy consumption evaluation of storage devices

Analytical models for performance and energy consumption evaluation of storage devices Eric Borba Universidade Federal de Pernambuco (UFPE) erb@cin.ufpe.br October, 2020