11209063
Integrated link/CPU voltage scaling for reducing energy consumption of parallel sparse matrix applications
Reducing power consumption is quickly becoming a first-class optimization metric for many high-performance parallel computing platforms. One of the techniques employed by many prior proposals along this direction is voltage scaling and past research used it on different components such as networks, CPUs, and memories. In contrast to most of the existent efforts on voltage scaling that target a single component (CPU, network or memory components), this paper proposes and experimentally evaluates a voltage/frequency scaling algorithm that considers CPU and communication links in a mesh network at the same time. More specifically, it scales voltages/frequencies of both CPUs in the network and the communication links among them in a coordinated fashion (instead of one after another) such that energy savings are maximized without impacting execution time. Our experiments with several tree-based sparse matrix computations reveal that the proposed integrated voltage scaling approach is very effective in practice and brings 13% and 17% energy savings over the pure CPU and pure communication link voltage scaling schemes, respectively. The results also show that our savings are consistent with the different network sizes and different sets of voltage/frequency levels
3053087
Dynamic Compilation for Reducing Energy Consumption of I/O-Intensive Applications
Tera-scale high-performance computing has enabled scientists to tackle very large and computationally challenging scientific problems, making the advancement of scientific discovery at a faster pace. However, as computing scales to levels never seen before, it also becomes extremely data intensive, I/O intensive, and energy consuming. Amongst these, I/O is becoming a major bottleneck, impeding the expected pace of scientific discovery and analysis of data. Furthermore, the applications are becoming increasingly dynamic in terms of their computation patterns as well as data access patterns to cope with larger problems and data sizes. Due to the complexities of systems and applications and their high energy consumptions, it is, therefore, very important to address research issues and develop dynamic techniques at the level of run-time systems and compilers to scale I/O in the right proportions. This paper presents the details of a dynamic compilation framework developed specifically for I/O-intensive large-scale applications. Our dynamic compilation framework includes a set of powerful I/O optimizations designed to minimize execution cycles and energy consumption, and generates results that are competitive with hand-optimized codes in terms of energy consumption.
1429882
Reducing Power through Compiler-Directed Barrier Synchronization Elimination
Interprocessor synchronization, while extremely important for ensuring execution correctness, can be very costly in terms of both power and performance overheads. Unfortunately, many parallelizing compilers are very conservative in inserting barrier synchronizations at the end of each and every parallel loop. This can lead to significant power consumption in chip multiprocessor based execution environments. This paper proposes a compiler-directed approach for eliminating such synchronization calls between neighboring parallel loops. It achieves its goal by partitioning loop iterations across processors such that each processor executes iterations from both the loops that access the same set of array elements. We implemented the proposed approach using an experimental compilation framework and made experiments with ten SPEC benchmark codes. Our experiments clearly show that the proposed compiler-directed approach is very effective and reduces energy overheads due to synchronizations by about 75.5%, and this corresponds to around 5.48% saving on average in overall energy consumption
8993751
A compiler-guided approach for reducing disk power consumption by exploiting disk access locality
Power consumption of large servers and clusters has recently been a popular research topic, since this issue is important from both technical and environmental viewpoints. The prior research proposed disk power management as one of the important ways of reducing overall power of a large system and considered both hardware-based and software-guided disk power reduction schemes. One of the common characteristics of the previously proposed approaches to disk power reduction is that they work with a given disk access pattern. In comparison, the goal of the approach proposed in this paper is to restructure application code using an optimizing compiler so that disk idle periods are lengthened. This in turn allows the underlying disk power management scheme to be more effective since such schemes usually prefer the long idle periods over the short ones. Our approach targets at large scientific applications that operate on disk-resident arrays using nested loops and exhibit regular data access patterns. To test the effectiveness of the proposed approach, we implemented it within an optimizing compiler and performed experiments with six data-intensive applications that manipulate disk-resident data. Our experimental analysis shows that the proposed approach is very successful in practice and reduces the total disk energy consumption on average by 18.17%, as compared to an execution without any disk power management, and by 11.55%, as compared to an execution that employs disks with low-power capabilities without our code restructuring approach.
9441131
Exposing disk layout to compiler for reducing energy consumption of parallel disk based systems
Disk subsystem is known to be a major contributor to overall power consumption of high-end parallel systems. Past research proposed several architectural level techniques to reduce disk power by taking advantage of idle periods experienced by disks. While such techniques have been known to be effective in certain cases, they share a common drawback: they operate in a reactive manner; i.e., they control disk power by observing past disk activity (e.g., idle and active periods) and estimating future ones. Consequently, they can miss opportunities for saving power and incur significant performance penalties, due to inaccuracies in predicting idle and active times. Motivated by this observation, this paper proposes and evaluates a compiler-driven approach to reducing disk power consumption of array-based scientific applications executing on parallel architectures. The proposed approach exposes disk layout information to the compiler, allowing it to derive disk access pattern, i.e., the order in which parallel disks are accessed. This paper demonstrates two uses of this information. First, we can do proactive disk power management, i.e., we can select the most appropriate power-saving strategy and disk preactivation strategy based on the compiler-predicted future idle and active periods of parallel disks. Second, we can restructure the application code to increase length of idle periods, which leads to better exploitation of available power-saving capabilities. We implemented both these approaches within an optimizing compiler and tested their effectiveness using a set of benchmark codes from the Spec2000 suite and a disk power simulator. Our results show that the compiler-driven disk power management is very promising. The experimental results also reveal that, while proactive disk power management is very effective, code restructuring for disk power achieves the best energy savings across all the benchmarks tested.
2552667
An evaluation of code and data optimizations in the context of disk power reduction
Disk power management is becoming increasingly important in high-end server and cluster type of environments that execute data-intensive applications. While hardware-only approaches (e.g., low-power modes supported by current disks) are successful to a certain extent, one also needs to consider the software side to achieve further energy savings. This paper first demonstrates that conventional data locality oriented code transformations are not sufficient for minimizing disk power consumption. The reason is that these optimizations do not take into account how disk-resident array data are laid out on the disk system, and consequently, fail to increase idle periods of disks, which is the primary metric using which disk power can be reduced. Instead, we propose a disk layout aware application optimization strategy that uses both code restructuring and data layout optimization. Our experimental evaluation with several benchmark codes reveal that the proposed strategy is very successful in reducing disk energy consumption without performing much worse than a pure data locality oriented scheme, as far as execution cycles are concerned. The experiments also show that the benefits coming from our approach increase with the increased number of disks; i.e., it scales very well.
9316311
Managing deadline miss ratio and sensor data freshness in real-time databases
The demand for real-time data services is increasing in many applications including e-commerce, agile manufacturing, and telecommunications network management. In these applications, it is desirable to execute transactions within their deadlines, i.e., before the real-world status changes, using fresh (temporally consistent) data. However, meeting these fundamental requirements is challenging due to dynamic workloads and data access patterns in these applications. Further, transaction timeliness and data freshness requirements may conflict. We define average/transient deadline miss ratio and new data freshness metrics to let a database administrator specify the desired quality of real-time data services for a specific application. We also present a novel QoS management architecture for real-time databases to support the desired QoS even in the presence of unpredictable workloads and access patterns. To prevent overload and support the desired QoS, the presented architecture applies feedback control, admission control, and flexible freshness management schemes. A simulation study shows that our QoS-aware approach can achieve a near zero miss ratio and perfect freshness, meeting basic requirements for real-time transaction processing. In contrast, baseline approaches fail to support the desired miss ratio and/or freshness in the presence of unpredictable workloads and data access patterns.
30591708
Infrastrukturentscheidungen in vernetzten Unternehmen Eine Wirtschaftlichkeitsanalyse am Beispiel von X.500 Directory Services
To support decisions concerning the planning and implementation of communication infrastructures between six German banking and insurance enterprises, costs and benefits of IT-standards are identified and data are empirically collected, taking X.500-based Directory Services as an example. Potential benefits amount to DM 24 million equivalent to a return on investment of 1100%.
15660031
Generalized performance management of multi-class real-time imprecise data services
The intricacy of real-time data service management increases mainly due to the emergence of applications operating in open and unpredictable environments, increases in software complexity, and need for performance guarantees. In this paper we propose an approach for managing the quality of service of real-time databases that provide imprecise and differentiated services, and that operate in unpredictable environments. Transactions are classified into service classes according to their level of importance. Transactions within each service class are further classified into subclasses based on their quality of service requirements. In this way transactions are explicitly differentiated according to their importance and quality of service requests. The performance evaluation shows that during overloads the most important transactions are guaranteed to meet their deadlines and that reliable quality of service is provided even in the face of varying load and execution time estimation errors
1721718
Recovering internet symmetry in distributed computing
This paper describes two systems to recover the Internet connectivity impaired by private networks and firewalls. These devices cause asymmetry in the Internet, making peer-to-peer computing difficult or even impossible. The Condor system is one of those that are severely impaired by the asymmetry. Compared to normal peer-to-peer computing applications, Condor has stricter requirements, which are representative to any grid computing. To make Condor seamlessly work across private networks and over firewalls, we designed and implemented Dynamic Port Forwarding (DPF) and Generic Connection Brokering (GCB). Both DPF and GCB satisfy the representative requirements. Furthermore DPF supports dedicated large clusters very well because it is simple, efficient, and highly scalable. On the other hand, GCB perfectly supports non-dedicated or personal clusters because it is independent to private network or firewall technologies and does not require airy administrative power to deploy it. In this paper, we describe the implementations of DPF and GCB and analyze them with respect to performance, deployability, security, and scalability.
10201757
Transparent access to Grid resources for user software
Grid computing promises access to large amounts of computing power, but so far adoption of Grid computing has been limited to highly specialized experts for three reasons. First, users are used to batch systems, and interfaces to Grid software are often complex and different to those in batch systems. Second, users are used to having transparent file access, which Grid software does not conveniently provide. Third, efforts to achieve wide-spread coordination of computers while solving the first two problems is hampered when clusters are on private networks. Here we bring together a variety of software that allows users to almost transparently use Grid resources as if they were local resources while providing transparent access to files, even when private networks intervene. As a motivating example, the BaBar Monte Carlo production system is deployed on a truly distributed environment, the European DataGrid, without any modification to the application itself. Copyright © 2005 John Wiley & Sons, Ltd.