Wednesday, 13 December 2017

Session 14: Work in Progress and Vision Papers II

Modelling Database Lock-Contention in Architecture-level Performance Simulation

Authors:

Philipp Merkle (Karlsruhe Institute of Technology)
Christian Stier (Karlsruhe Institute of Technology)

Abstract:

Databases are the origin of many performance problems found in transactional information systems. Performance suffers especially when databases employ locking to isolate concurrent transactions. Software performance models therefore need to reflect lock contention in order to be a credible source for guiding design decisions. We propose a hybrid simulation approach that integrates a novel locking model into the Palladio software architecture performance simulator. Our model operates on a row level and is tailored to be used with architecture-level performance models. An experimental evaluation leads to promising results close to the measured performance.

DOI: 10.1145/2568088.2576762

Full text: PDF

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Benchmarking Graph-Processing Platforms: A Vision

Authors:

Yong Guo (TU Delft)
Ana Lucia Varbanescu (University of Amsterdam)
Alexandru Iosup (TU Delft)
Claudio Martella (VU University Amsterdam)
Theodore L. Willke (Intel Corporation)

Abstract:

Processing graphs, especially at large scale, is an increasingly useful activity in a variety of business, engineering, and scientific domains. Already, there are tens of graph-processing platforms, such as Hadoop, Giraph, GraphLab, etc., each with a different design and functionality. For graph-processing to continue to evolve, users have to find it easy to select a graph-processing platform, and developers and system integrators have to find it easy to quantify the performance and other non-functional aspects of interest. How- ever, the state of performance analysis of graph-processing platforms is still immature: there are few studies and, for the few that exist, there are few similarities, and relatively little understanding of the impact of dataset and algorithm diversity on performance. Our vision is to develop, with the help of the performance-savvy community, a comprehensive benchmarking suite for graph- processing platforms. In this work, we take a step in this direction, by proposing a set of seven challenges, summarizing our previous work on performance evaluation of distributed graph-processing platforms, and introducing our on-going work within the SPEC Research Group’s Cloud Working Group.

DOI: 10.1145/2568088.2576761

Full text: PDF

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Real-Time Multi-Cloud Management Needs Application Awareness

Authors:

John Chinneck (Carleton University)
Marin Litoiu (York University)
Murray Woodside (Carleton University)

Abstract:

Current cloud management systems have limited awareness of the user application, and application managers have no awareness of the state of the cloud. For applications with strong real-time requirements, distributed across new multi-cloud environments, this lack of awareness hampers response-time assurance, efficient deployment and rapid adaptation to changing workloads. This paper considers what forms this awareness may take, how it can be exploited in managing the applications and the clouds, and how it can influence cloud architecture.

DOI: 10.1145/2568088.2576763

Full text: PDF

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