Eduardo Pinheiro

Conserving disk energy in network servers

In this paper we study four approaches to conserving disk energy in high-performance network servers. The first approach is to leverage the extensive work on laptop disks and power disks down during periods of idleness. The second approach is to replace high-performance disks with a set of lower power disks that can achieve the same performance and reliability. The third approach is to combine high-performance and laptop disks, such that only one of these two sets of disks is powered on at a time. This approach requires the mirroring (and coherence) of all disk data on the two sets of disks. Finally, the fourth approach is to use multi-speed disks, such that each disk is slowed down for lower energy consumption during periods of light load. We demonstrate that the fourth approach is the only one that can actually provide energy savings for network servers. In fact, our results for Web and proxy servers show that the fourth approach can provide energy savings of up to 23%, in comparison to conventional servers, without any degradation in server performance.

Dynamic cluster reconfiguration for power and performance

In this chapter we address power conservation for clusters of workstations or PCs. Our approach is to develop systems that dynamically turn cluster nodes on - to be able to handle the load imposed on the system efficiently - and off - to save power under lighter load. The key component of our systems is an algorithm that makes cluster reconfiguration decisions by considering the total load imposed on the system and the power and performance implications of changing the current configuration. The algorithm is implemented in two common cluster-based systems: a network server and an operating system for clustered cycle servers. Our experimental results are very favorable, showing that our systems conserve both power and energy in comparison to traditional systems.

Exploiting redundancy to conserve energy in storage systems

This paper makes two main contributions. First, it introduces Diverted Accesses, a technique that leverages the redundancy in storage systems to conserve disk energy. Second, it evaluates the previous (redundancy-oblivious) energy conservation techniques, along with Diverted Accesses, as a function of the amount and type of redundancy in the system. The evaluation is based on novel analytic models of the energy consumed by the techniques. Using these energy models and previous models of reliability, availability, and performance, we can determine the best redundancy configuration for new energy-aware storage systems. To study Diverted Accesses for realistic systems and workloads, we simulate a wide-area storage system under two file-access traces. Our modeling results show that Diverted Accesses is more effective and robust than the redundancy-oblivious techniques. Our simulation results show that our technique can conserve 20-61% of the disk energy consumed by the wide-area storage system.

Application transformations for energy and performance-aware device management

Energy conservation without performance degradation is an important goal for battery-operated computers, such as laptops and handheld assistants. In this paper we determine the potential benefits of application-supported device management for optimizing energy and performance. In particular, we consider application transformations that increase device idle times and inform the operating system about the length of each upcoming period of idleness. We assess the potential energy and performance benefits of this type of application support for a laptop disk. Furthermore, we propose and evaluate a compiler framework for performing the transformations automatically for a disk device. Our experimental results demonstrate that unless applications are transformed, they cannot accrue any of the predicted benefits. In addition, they show that our compiler can produce almost the same performance and energy results that we obtain by hand-modifying applications. Overall, we find that the transformations we propose can reduce disk energy consumption from 55% to 89% with only a small degradation in performance.

Code transformations for energy-efficient device management

Energy conservation without performance degradation is an important goal for battery-operated computers, such as laptops and hand-held assistants. We study application-supported device management for optimizing energy and performance. In particular, we consider application transformations that increase device idle times and inform the operating system about the length of each upcoming, period of idleness. We use modeling and experimentation to assess the potential energy and performance benefits of this type of application support for a laptop disk. Furthermore, we propose and evaluate a compiler framework for performing the transformations automatically. Our main modeling results show that the transformations are potentially beneficial. However, our experimental results with six real laptop applications demonstrate that, unless applications are transformed, they cannot accrue any of the predicted benefits. In addition, they show that our compiler can produce almost the same performance and energy results as hand-modifying applications. Overall, we find that the transformations can reduce disk energy consumption from 55 percent to 89 percent with degradation in performance of at most 8 percent.

Nomad: a scalable operating system for clusters of uni- and multiprocessors

The recent improvements in workstation and interconnection network performance have popularized the clusters of off-the-shelf workstations. However, the usefulness of these clusters is yet to be fully exploited, mostly due to the inadequate management of cluster resources implemented by current distributed operating systems. In order to eliminate this problem and approach the computational power of large clusters of workstations, in this paper we propose Nomad, an efficient operating system for clusters of uni and/or multiprocessors. Nomad includes several important characteristics for modern cluster-oriented operating systems: scalability, efficient resource management across the cluster, efficient scheduling of parallel and distributed applications, distributed I/O, fault detection and recovery, protection, and backward compatibility. Some of the mechanisms used by Nomad, such as process checkpointing and migration, can be found in previously proposed systems. However, our system stands out for its strategy for disseminating information across the cluster and its efficient management of all cluster resources. In addition, Nomad is highly scalable as it uses neither centralized control nor extra messages to implement its functionality, taking advantage of the I/O traffic associated with its distributed file system. Our preliminary evaluation of the load balancing aspect of Nomad shows that the pattern of file accesses in our distributed Ale system allows for efficient and scalable load balancing. Our main conclusion is that the complete implementation of Nomad will most likely be efficient and will be a nice platform for future research on operating systems for clusters of workstations.

Application-supported device management for energy and performance

Energy conservation without performance degradation is an important goal for battery-operated computers, such as laptops and hand-held assistants. In this paper we determine the potential benefits of application-supported device management for optimizing energy and performance. In particular, we consider application transformations that increase device idle times and inform the operating system about the length of each upcoming period of idleness. We use modeling and experimentation to assess the potential energy and performance benefits of this type of application support for a laptop disk. Our main modeling results show that these benefits are significant. Our experimental results demonstrate that unless applications are transformed, they cannot accrue any of the predicted benefits. Overall, we find that the transformations can reduce disk energy consumption by as much as 89% with only a small degradation in performance.