Performance evaluation of enhancement of the layered self-scheduling approach for heterogeneous multicore cluster systems

Previously we have proposed a Layered Self-Scheduling (LSS) approach that is a hybrid MPI and OpenMP based loop self-scheduling approach for dealing with the heterogeneity problem on a cluster system consisting of multi-core compute nodes, where the allocation functions of several well-known schemes have been modified for better performance. Though LSS provides better performance than the conventional self-scheduling schemes, we found the performance can be improved further after our comprehensive experiments and analyses. The newly proposed task scheduling strategy, called Enhanced Layered Self-Scheduling (ELSS), aims at how to utilize the compute powers of multiple processor cores more efficiently in the master compute node and how to schedule tasks to have more stable performance improvements. We have evaluated the new task scheduling strategy by three benchmark applications: Matrix Multiplication, Monte Carlo Integration, and Mandelbrot Set Computation. It is recommended that the global scheduler adopts Guided Self-Scheduling (GSS) for all, and the local scheduler adopts the static scheme for applications with regular workload distribution but any scheme for applications with irregular workload distribution. Experimental results show the best speedups obtained by ELSS for the three benchmark programs are 1.373, 13.34 and 2.4, respectively, compared with that scheduled by LSS.     

Differentiated Service Provision in Optical CDMA Network Using Power Control

A simple scheme to use power control for differentiated service provision is proposed for the optical code-division multiple-access network. The main advantages of this scheme are: 1) Interference from other users can be eliminated theoretically. 2) The decoder with simple configuration can be used as compared to that in a previous power control scheme. 3) The design procedure of various service requirements in one network is simplified.      

Using hybrid MPI and OpenMP programming to?optimize communications in parallel loop self-scheduling schemes for multicore PC clusters

Recently, a series of parallel loop self-scheduling schemes have been proposed, especially for heterogeneous cluster systems. However, they employed the MPI programming model to construct the applications without considering whether the computing node is multicore architecture or not. As a result, every processor core has to communicate directly with the master node for requesting new tasks no matter the fact that the processor cores on the same node can communicate with each other through the underlying shared memory. To address the problem of higher communication overhead, in this paper we propose to adopt hybrid MPI and OpenMP programming model to design two-level parallel loop self-scheduling schemes. In the first level, each computing node runs an MPI process for inter-node communications. In the second level, each processor core runs an OpenMP thread to execute the iterations assigned for its resident node. Experimental results show that our method outperforms the previous works.     

Grey prediction fuzzy control for pH processes in the food industry

Proper regulation of pH value is an important issue in the food industry for quality production. A food pH process usually has non-linear dynamics with system uncertainty. This study treats the pH regulation process of a reactor tank as a grey box with partially known system information. The behaviour of the process is predicted one-step ahead with a first-order grey model. A fuzzy controller takes the prediction together with the current system response to regulate the discharge of base (NaOH) or acid (HCl) solution into the reactor tank to arrive at a desired pH value. The integrated grey prediction fuzzy control (GPFC) strategy is simple in control-law derivation and system implementation and is efficient in computation. The developed GPFC was validated with perform base/acid titration and continuous acidification/deacidification control. The controlled system response error was trivial in the titration and was less than 1% in the continuous control under proper agitation of the reactants. The system was used to control Acetobacter xylinum fermentation for cellulose production. The GPFC scheme exerted smooth control action, achieved a trivial steady-state error in pH control, and yielded more cellulose and acetic acid products but consumed much less material than PID or manual control.     

Wavelength–time optical CDMA scheme adopting commercial 2m × 2m arrayed waveguide gratings

One new code family with asymptotically optimal cardinality is proposed for high-speed OCDMA networks. This code family has short code lengths and can adopt commercial 2^m × 2^m arrayed waveguide gratings for coder implementation (m is positive integer). The performance analysis shows that the proposed code family has improved spectral efficiencies as compared to wavelength/time codes generated from other coding schemes with asymptotically optimal cardinalities.     

Performance analysis of WS-EWC coded optical CDMA networks with/without LDPC codes

One extended Welch-Costas (EWC) code family for the wavelength-division-multiplexing/spectral-amplitude coding (WDM/SAC; WS) optical code-division multiple-access (OCDMA) networks is proposed. This system has a superior performance as compared to the previous modified quadratic congruence (MQC) coded OCDMA networks. However, since the performance of such a network is unsatisfactory when the data bit rate is higher, one class of quasi-cyclic low-density parity-check (QC-LDPC) code is adopted to improve that. Simulation results show that the performance of the high-speed WS-EWC coded OCDMA network can be greatly improved by using the LDPC codes.     

An integrated security-aware job scheduling strategy for large-scale computational grids

All existing fault-tolerance job scheduling algorithms for computational grids were proposed under the assumption that all sites apply the same fault-tolerance strategy. They all ignored that each grid site may have its own fault-tolerance strategy because each site is itself an autonomous domain. In fact, it is very common that there are multiple fault-tolerance strategies adopted at the same time in a large-scale computational grid. Various fault-tolerance strategies may have different hardware and software requirements. For instance, if a grid site employs the job checkpointing mechanism, each computation node must have the following ability. Periodically, the computational node transmits the transient state of the job execution to the server. If a job fails, it will migrate to another computational node and resume from the last stored checkpoint. Therefore, in this paper we propose a genetic algorithm for job scheduling to address the heterogeneity of fault-tolerance mechanisms problem in a computational grid. We assume that the system supports four kinds fault-tolerance mechanisms, including the job retry, the job migration without checkpointing, the job migration with checkpointing, and the job replication mechanisms. Because each fault-tolerance mechanism has different requirements for gene encoding, we also propose a new chromosome encoding approach to integrate the four kinds of mechanisms in a chromosome. The risk nature of the grid environment is also taken into account in the algorithm. The risk relationship between jobs and nodes are defined by the security demand and the trust level. Simulation results show that our algorithm has shorter makespan and more excellent efficiencies on improving the job failure rate than the Min–Min and sufferage algorithms.     

Extending FuzzyCLIPS for parallelizing data-dependent fuzzy expert systems

FuzzyCLIPS is a rule-based programming language and it is very suitable for developing fuzzy expert systems. However, it usually requires much longer execution time than algorithmic languages such as C and Java. To address this problem, we propose a parallel version of FuzzyCLIPS to parallelize the execution of a fuzzy expert system with data dependence on a cluster system. We have designed some extended parallel syntax following the original FuzzyCLIPS style. To simplify the programming model of parallel FuzzyCLIPS, we hide, as much as possible, the tasks of parallel processing from programmers and implement them in the inference engine by using MPI, the de facto standard for parallel programming for cluster systems. Furthermore, a load balancing function has been implemented in the inference engine to adapt to the heterogeneity of computing nodes. It will intelligently allocate different amounts of workload to different computing nodes according to the results of dynamic performance monitoring. The programmer only needs to invoke the function in the program for better load balancing. To verify our design and evaluate the performance, we have implemented a human resource website. Experimental results show that the proposed parallel FuzzyCLIPS can garner a superlinear speedup and provide a more reasonable response time.     

Interference elimination in optical CDMA passive optical network using multiple-weight codewords

A spectral-amplitude coding optical code-division multiple access network for multimedia transmissions is proposed. This scheme allows users with different service requirements to transmit data without interference theoretically, and the number of service classes is flexible and can be any integer theoretically if the required light sources and optical components are available. Because the corresponding encoder/decoder uses arrayed waveguide gratings of smaller physical sizes, the imperfect phenomenon such as crosstalk in the encoders is alleviated and the realization is more practical for the application of passive optical networks. When the bit error rate is smaller than 10⁻⁹, the effective number of active users in this scheme is larger than that of classical SAC schemes supporting no differentiated service.