How Vladimir Putin’s Divorce Story Was Constructed and Received, or When the President Divorced His Wife and Married the Country Instead

When the Russian president divorced his wife in 2013, social media crowds coined plenty of the Internet memes to interpret the news. Anastasia Denisova, Doctoral Researcher at CAMRI, examined the framing of the story in traditional and new media and came to the surprising findings.

Letters to the editor

The author states his opinion that the most valuable contribution of the July 2007 issue is Gene Amdahl's new paper, which he thinks will probably become as popular as the Amdahl paper reprinted in the same issue since it provides much needed clarifications, and most notably includes the original 'law' formula as presented by Amdahl four decades ago.

Corrections

Summary form only given, as follows. In Vol. 12, no. 3 (Summer 2007), page 9, bottom of the left column, in 'Computer Architecture and Amdahl??s Law' by Gene Amdahl, the claim about invalidating Amdahl??s Law in 1988 came from a team at Sandia National Laboratories, and not Los Alamos. The correct text should read: "Several years later I was informed of a proof that Amdahl's Law was invalidated by someone at Sandia National Laboratories, where a number of computers interconnected as an Ncube by communication lines, but with each computer also connected to I/O devices for loading the operating system, initial data, and results." On page 20 of the same issue, in the second sentence of the diagram explanation note by Justin Rattner, the percentage figures for the sequential and the system coordination parts of the workload were interchanged. The correct version of this sentence should read: "assuming a fixed sized problem, Amdahl speculated that most programs would require at least 10% of the computation to be sequential (only one instruction executing at a time), with overhead due to interprocessor coordination averaging 25%."

Distributed Agent-Based Load Balancer for Cloud Computing

In this paper we present a concept of an agent-based strategy to allocate services on a Cloud system without overloading nodes and maintaining the system stability with minimum cost. To provide a base for our research we specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. We also present an early version of simulation environment and a prototype of agent-based load balancer implemented in functional language Scala and Akka framework.

Workload Schedulers - Genesis, Algorithms and Comparisons

In this article we provide brief descriptions of three classes of schedulers: Operating Systems Process Schedulers, Cluster Systems, Jobs Schedulers and Big Data Schedulers. We describe their evolution from early adoptions to modern implementations, considering both the use and features of algorithms. In summary, we discuss differences between all presented classes of schedulers and discuss their chronological development. In conclusion, we highlight similarities in the focus of scheduling strategies design, applicable to both local and distributed systems.

Towards an Application-Specific Thermal Energy Model of Current Processors

Recent developments of high-end processors recognize temperature monitoring and tuning as one of the main challenges towards achieving higher performance given the growing power and temperature constraints. To address this challenge, one needs both suitable thermal energy abstraction and corresponding instrumentation. Our model is based on application-specific parameters such as power consumption, execution time, and asymptotic temperature as well as hardware-specific parameters such as half time for thermal rise or fall. As observed with our out-of-band instrumentation and monitoring infrastructure, the temperature changes follow a relatively slow capacitor-style charge-discharge process. Therefore, we use the lumped thermal model that initiates an exponential process whenever there is a change in processor’s power consumption. Initial experiments with two codes – Firestarter and Nekbone – validate our thermal energy model and demonstrate its use for analyzing and potentially improving the application-specific balance between temperature, power, and performance.

Context-aware Approach for Determining the Threshold Price in Name-Your-Own-Price Channels

Key feature of a context-aware application is the ability to adapt based on the change of context. Two approaches that are widely used in this regard are the context-action pair mapping where developers match an action to execute for a particular context change and the adaptive learning where a context-aware application refines its action over time based on the preceding action’s outcome. Both these approaches have limitation which makes them unsuitable in situations where a context-aware application has to deal with unknown context changes. In this paper we propose a framework where adaptation is carried out via concurrent multi-action evaluation of a dynamically created action space. This dynamic creation of the action space eliminates the need for relying on the developers to create context-action pairs and the concurrent multi-action evaluation reduces the adaptation time as opposed to the iterative approach used by adaptive learning techniques. Using our reference implementation of the framework we show how it could be used to dynamically determine the threshold price in an e-commerce system which uses the name-your-own-price (NYOP) strategy.

A Meta-Heuristic Load Balancer for Cloud Computing Systems

This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded with the outputs of other meta-heuristic algorithms.