Among the high-radix and low-diameter networks, fat-tree topology is commonly used in high-performance computing (HPC) and datacenter systems. Resource and job management on HPC systems is critically important to mitigate application interference in order to achieve high system performance and utilization. Preliminary studies have shown the effect of job placement on parallel scientific applications performance in fat-tree network. In this work we explore the joint effects of job placement and network routing aware of applications communication pattern on fat-tree system. Applications can be classified into various groups according to the communication patterns. We further combine various job placement policies and routing algorithms and create six different configurations. The system performance is analyzed using communication, hops, traffic, and saturation data by performing fine-grained high-fidelity discrete event-driven simulation. Initial experimentation shows that the performance of HPC applications not only is related with the communication pattern, but also relies on the job placement and network routing on fat-tree systems.
The application of physical layer security in wireless ad hoc networks (WANETs) has attracted considerable academic attention recently. However, the available studies mainly focus on the single-hop and two-hop network scenarios, and the price in terms of degradation of communication quality of service (QoS) caused by improving security is largely uninvestigated. As a step to address these issues, this paper explores the physical layer security-aware routing and performance tradeoffs in a multi-hop WANET. Specifically, for any given end-to-end path in a general multi-hop WANET, we first derive its connection outage probability (COP) and secrecy outage probability (SOP) in closed-form, which serve as the performance metrics of communication QoS and transmission security, respectively. Based on the closed-form expressions, we then study the QoS-security tradeoffs to minimize COP (resp. SOP) conditioned on that SOP (resp. COP) is guaranteed. With the help of analysis of a given path, we further propose the routing algorithms which can achieve the optimal performance tradeoffs for any pair of source and destination nodes in a distributed manner. Finally, simulation and numerical results are presented to validate the efficiency of our theoretical analysis, as well as to illustrate the QoS-security tradeoffs and the routing performance.
The employment rate is an effective measure of the performance of an economy The changes of employment rate in EU are: The development of employment rate is unbalance in individual Member States, and change is a little; the trend to lower employment for young people is evident; the employment rate of women increases; the employment rate of old people is different in Member States Factors such as taxation system, the way benefits operate, regulations on business and labor can be conductive to more employment or discourage it The differ in each Member State and the particular way they interact is important in determining their overall impact
As systems scale toward exactable, many resources will become increasingly constrained. While some of these resources have historically been explicitly allocated, many -- such as network bandwidth, I/O bandwidth, or power -- have not. As systems continue to evolve, we expect many such resources to become explicitly managed. This change will pose critical challenges to resource management and job scheduling. In this paper, we explore the potentiality of relaxing network allocation constraints for Blue Gene systems. Our objectives to improve the batch scheduling performance, where the partition-based interconnect architecture provides a unique opportunity to explicitly allocate network resources to jobs. This paper makes three major contributions. The first is substantial benchmarking of parallel applications, focusing on assessing application sensitivity to communication bandwidth at large scale. The second is two new scheduling schemes using relaxed network allocation and targeted at balancing individual job performance with overall system performance. The third is a comparative study of our scheduling schemes versus the existing one under different workloads, using job traces collected from the 48-rack Mira, an IBM Blue Gene/Q system at Argonne National Laboratory.
Achieving higher spectrum utilization, auction-based mechanisms has been regarded as a popular tool in dynamic spectrum access (DSA). Recently, Sybil attacks in auction-based DSA mechanisms have been investigated, where a cheating bidder can manipulate an auction by submitting bids under multiple fake identities. Existing Sybil-proof mechanisms in DSA are limited to prevent Sybil attacks from primary users (PUs) or secondary users (SUs). However, both of PUs and SUs may perform Sybil attacks in DSA, i.e., double Sybil attacks. The challenge of solving the double Sybil attacks is that fictitious identities and fake bids can directly affect allocation results, but the malicious bidders cannot be straightforwardly distinguished from all bidders. To resist the double Sybil attacks, we propose STEAM, the first double Sybil-proof and two-dimensional Truthful spEctrum Auction Mechanism for DSA. Specifically, STEAM merges suspicious buyers based on geographic characteristics and sorts sellers by a bid-independent sorting method to minimize the impact of untruthful bids and Sybil attacks on the allocation results. Theoretical analysis and extensive evaluations prove that STEAM is double Sybil-proof, two-dimensional truthful, individual rational and budget-balanced, while the performance loss in various metrics within 8% compared to the existing auction-based mechanisms.
Network contention between concurrently running jobs on HPC systems is a primary cause of performance variability. Optimizing job allocation and avoiding network sharing are hence crucial to alleviate the potential performance degradation. In order to do so effectively, an understanding of the interference among concurrently running jobs, their communication patterns, and contention in the network is required. In this work, we choose three representative HPC applications from the DOE Design Forward Project and conduct detailed simulations on a torus network model to analyze both intra-and interjob interference. By scrutinizing the communication behaviors of these applications, we identify relationships between these behaviors and the possible interference introduced by different job placement policies. Our analyses illuminate a path toward communication pattern awareness in job placement on HPC systems.
Dragonfly network is widely used in modern high-performance computing systems. On this network, however, interference caused by network sharing can lead to significant network congestion and degraded performance. In this work, we present a comparative analysis of intra-application interference on applications with nearest neighbor communication, considering various placement strategies. Our results demonstrate that intra-application interference is basically a trade-off between localized communication and balanced network. We further develop alternative job placement policies with the objective to balance the trade-off between localized communication and balanced network. The results demonstrate that our proposed strategies can effectively balance the trade-off and hence reduce intra-application interference on Dragonfly network.
The research literature to date mainly aimed at reducing energy consumption in HPC environments. In this paper we propose a job power aware scheduling mechanism to reduce HPC's electricity bill without degrading the system utilization. The novelty of our job scheduling mechanism is its ability to take the variation of electricity price into consideration as a means to make better decisions of the timing of scheduling jobs with diverse power profiles. We verified the effectiveness of our design by conducting trace-based experiments on an IBM Blue Gene/P and a cluster system as well as a case study on Argonne's 48-rack IBM Blue Gene/Q system. Our preliminary results show that our power aware algorithm can reduce electricity bill of HPC systems as much as 23%.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
