An on-line algorithm for checkpoint placement

Checkpointing is a common technique for reducing the time to recover from faults in computer systems. By saving intermediate states of programs in a reliable storage, checkpointing enables to reduce the lost processing time caused by faults. The length of the intervals between checkpoints affects the execution time of programs. Long intervals lead to long re-processing time, while too frequent checkpointing leads to high checkpointing overhead. In this paper we present an on-line algorithm for placement of checkpoints. The algorithm uses on-line knowledge of the current cost of a checkpoint when it decides whether or not to place a checkpoint. We show how the execution time of a program using this algorithm can be analyzed. The total overhead of the execution time when the proposed algorithm is used is smaller than the overhead when fixed intervals are used. Although the proposed algorithm uses only on-line knowledge about the cost of checkpointing, its behavior is close to the off-line optimal algorithm that uses a complete knowledge of checkpointing cost

Analysis of checkpointing schemes for multiprocessor systems

Parallel computing systems provide hardware redundancy that helps to achieve low cost fault-tolerance, by duplicating the task into more than a single processor, and comparing the states of the processors at checkpoints. This paper suggests a novel technique, based on a Markov Reward Model (MRM), for analyzing the performance of checkpointing schemes with task duplication. We show how this technique can be used to derive the average execution time of a task and other important parameters related to the performance of checkpointing schemes. Our analytical results match well the values we obtained using a simulation program. We compare the average task execution time and total work of four checkpointing schemes, and show that generally increasing the number of processors reduces the average execution time, but increases the total work done by the processors. However, in cases where there is a big difference between the time it takes to perform different operations, those results can change

Efficient checkpointing over local area networks

Parallel and distributed computing on clusters of workstations is becoming very popular as it provides a cost effective way for high performance computing. In these systems, the bandwidth of the communication subsystem (Using Ethernet technology) is about an order of magnitude smaller compared to the bandwidth of the storage subsystem. Hence, storing a state in a checkpoint is much more efficient than comparing states over the network. In this paper we present a novel checkpointing approach that enables efficient performance over local area networks. The main idea is that we use two types of checkpoints: compare-checkpoints (comparing the states of the redundant processes to detect faults) and store-checkpoints (where the state is only stored). The store-checkpoints reduce the rollback needed after a fault is detected, without performing many unnecessary comparisons. As a particular example of this approach we analyzed the DMR checkpointing scheme with store-checkpoints. Our main result is that the overhead of the execution time can be significantly reduced when store-checkpoints are introduced. We have implemented a prototype of the new DMR scheme and run it on workstations connected by a LAN. The experimental results we obtained match the analytical results and show that in some cases the overhead of the DMR checkpointing schemes over LAN's can be improved by as much as 20%

Performance optimization of checkpointing schemes with task duplication

In checkpointing schemes with task duplication, checkpointing serves two purposes: detecting faults by comparing the processors' states at checkpoints, and reducing fault recovery time by supplying a safe point to rollback to. In this paper, we show that, by tuning the checkpointing schemes to a given architecture, a significant reduction in the execution time can be achieved. The main idea is to use two types of checkpoints: compare-checkpoints (comparing the states of the redundant processes to detect faults) and store-checkpoints (storing the states to reduce recovery time). With two types of checkpoints, we can use both the comparison and storage operations in an efficient way and improve the performance of checkpointing schemes. Results we obtained show that, in some cases, using compare and store checkpoints can reduce the overhead of DMR checkpointing schemes by as much as 30 percent

Competitive Equilibrium of an Industry with Labor Managed Firms and Price Risk

This paper studies the effect of output-price uncertainty in an industry comprised of labor-managed firms (LMFs) in which the number of LMFs and their membership are determined endogenously. The exit condition for a risk-averse LMF member is formulated and the effect of various economic variables on the equilibrium quantities and prices are examined. We find that the equilibrium in our setting is similar to the one that emerges in a ‘capitalistic’ economy where firms are owned by profit-maximizing agents. However, the effects of increases in risk and risk aversion differ from those found in a short-run analysis of a single LMF.Labor Managed Firms, Cooperatives, Price Risk, Risk Aversion, Long-Run., Agribusiness,

REGULATING IRRIGATION VIA BLOCK-RATE PRICING: AN ECONOMETRIC ANALYSIS

In this paper, we adapt Burtless and Hausman's (1978) methodology in order to estimate farmer's demand for irrigation water under increasing block-rate tariffs and empirically assess its effect on aggregate demand and inter-farm allocation efficiency. This methodology overcomes the technical challenges raised by increasing block rate pricing and accounts for both observed and unobserved technological heterogeneity among farmers. Employing a micro panel data documenting irrigation levels and prices in 185 Israeli agricultural communities in the period 1992-1997 we estimate water demand elasticity at -0.3 in the short run (the effect of a price change on demand within a year of implementation) and -0.46 in the long run. We also find that, in accordance with common belief, switching from a single to a block price regime, yields a 7% reduction in average water use while maintaining the same average price. However, based on our simulations we estimate that the switch to block prices will result in a loss of approximately 1% of agricultural output due to inter-farm allocation inefficiencies.Block-Rate Pricing, Irrigation, C13, Q15, Q28, Resource /Energy Economics and Policy,

An Online Algorithm for Checkpointing Placement

Checkpointing is a common technique for reducing the time to recover from faults in computer systems. By saving intermediate states of programs in a reliable storage, check pointing enables to reduce the lost processing time caused by faults. The length of the intervals between checkpoints affects the execution time of programs. Long intervals lead to long re-processing time, while too frequent checkpoint- iizg leads to high checkpointing overhead. In this paper we present an on-line algorithm for placement of checkpoints. The algorithm uses on-line knowledge of the current cost of a checkpoint when it decides whether or not to place a checkpoint. We show how the execution time of a program using this algorithm can be analyzed. The total overhead of the execution time when the proposed algorithm is used is smaller than the overhead when fixed intervals are used. Although the proposed algorithm uses only on-line knowledge about the cost of checkpointing, its behavior is close to the off-line optimal algorithm that uses a complete knowledge of checkpointing cost

Performance Optimization of Checkpointing Schemes with Task Duplication

Checkpointing schemes enable fault-tolerant parallel and distributed computing by leveraging the redundancy in hardware and software resources. In these systems, checkpointing serves two purposes: it helps in detecting faults by comparing the processors states at checkpoints, and it facilitates the reduction of fault recovery time by supplying a safe point to rollback to. The efficiency of checkpointing schemes is influenced by the time it takes to perform the comparisons and to store the states. The fact that checkpoints consist of both storing of states and comparison between states, with conflicting objectives regarding the frequency of those operations, limits the performance of current checkpointing schemes. In this paper we show that by tuning the checkpointing schemes to a given architecture, a significant reduction in the execution time can be achieved. We will present both analytical results and experimental results that were obtained on a cluster of workstations and a parallel computer. The main idea is to use two types of checkpoints: compare-checkpoints (comparing the states of the redundant processes to detect faults) and store-checkpoints (storing the states to reduce recovery time). With two types of checkpoints, we can use both the comparison and storage operations in an efficient way and improve the performance of checkpointing schemes. As a particular example of this approach we analyzed the DMR checkpointing scheme with store and compare checkpoints on two types of architectures, one where the comparison time is much higher than the store time (like a cluster of workstations connected by a LAN) and one where the store time is much higher than the comparison time (like the Intel Paragon supercomputer). We have implemented a prototype of the new DMR schemes and run it on workstations connected by a LAN and on the Intel Paragon supercomputer. The experimental results we obtained match the analytical results and show that in some cases the overhead of the DMR checkpointing schemes on both architectures can be improved by as much as 40%

Efficacy of methylsulfonylmethane supplementation on osteoarthritis of the knee: a randomized controlled study

BACKGROUND: Patients with osteoarthritis (OA) take a variety of health supplements in an attempt to reduce pain and improve function. The aim of this study was to determine the efficacy of methylsulfonylmethane (MSM) in treating patients with knee OA. METHODS: This study was a prospective, randomized, double-blind, controlled clinical trial. Forty nine men and women 45-90 (mean 68 ± SD 7.3) years of age with knee OA according to the American College of Rheumatology clinical criteria for OA of the knee and with radiographic confirmed knee OA were enrolled in the study and randomly assigned into 2 groups: One received MSM in doses of 1.125 grams 3 times daily for 12 weeks and the other received a placebo in the same dosing frequency. The primary outcomes were the WOMAC Osteoarthritis Index for pain, stiffness and physical function, the Aggregated Locomotor Function (ALF) test that evaluates each patient's physical function, the SF-36 quality of life health survey and the visual-analogue-scale (VAS) for pain. The secondary outcomes were Knee Society Clinical Rating System for Knee Score (KSKS) and Function Score (KSFS). Patients were assessed at baseline, 6 weeks and 12 weeks. All continuous variables were tested by the Kolmogorov-Smirnov test for Normal distribution. Changes within the groups and differences between the groups were calculated by repeated measures of analysis (ANOVA) with one nested variable. RESULTS: There were significant differences between treatment groups over time in WOMAC physical function (14.6 mm [CI: 4.3, 25.0]; p = 0.04) and in WOMAC total score (15.0 mm [CI: 5.1, 24.9]; p = 0.03). Treatment groups did not differ significantly in WOMAC pain (12.4 mm [CI: 0.0, 24.8]); p = 0.08) or WOMAC stiffness (27.2 mm [CI: 8.2, 46.2]; p = 0.08). There was a non-significant difference in SF-36 total score between treatment groups (11.6 [CI: 1.0, 22.1]; p = 0.54). A significant difference was found between groups in VAS for pain (0.7 s [CI: -0.9, 2.4]; p = 0.05). Secondary outcomes showed non-significant differences between the two groups. CONCLUSIONS: Patients with OA of the knee taking MSM for 12 weeks showed an improvement in pain and physical function. These improvements, however, are small and it is yet to be determined if they are of clinical significance. TRIAL REGISTRATION: ClinicalTrials.gov: NCT0118821