A taxonomy of application scheduling tools for high performance cluster computing

Application scheduling plays an important role in high-performance cluster computing. Application scheduling can be classified as job scheduling and task scheduling. This paper presents a survey on the software tools for the graph-based scheduling on cluster systems with the focus on task scheduling. The tasks of a parallel or distributed application can be properly scheduled onto multi-processors in order to optimize the performance of the program (e.g., execution time or resource utilization). In general, scheduling algorithms are designed based on the notion of task graph that represents the relationship of parallel tasks. The scheduling algorithms map the nodes of a graph to the processors in order to minimize overall execution time. Although many scheduling algorithms have been proposed in the literature, surprisingly not many practical tools can be found in practical use. After discussing the fundamental scheduling techniques, we propose a framework and taxonomy for the scheduling tools on clusters. Using this framework, the features of existing scheduling tools are analyzed and compared. We also discuss the important issues in improving the usability of the scheduling tools. This work is supported by the Hong Kong Polytechnic University under grant H-ZJ80 and by NASA Ames Research Center by a cooperative grant agreement with the University of Texas at Arlington. Jiannong Cao received the BSc degree in computer science from Nanjing University, Nanjing, China in 1982, and the MSc and the Ph.D degrees in computer science from Washington State University, Pullman, WA, USA, in 1986 and 1990 respectively. He is currently an associate professor in Department of Computing at the Hong Kong Polytechnic University, Hong Kong. He is also the director of the Internet and Mobile Computing Lab in the department. He was on the faculty of computer science at James Cook University and University of Adelaide in Australia, and City University of Hong Kong. His research interests include parallel and distributed computing, networking, mobile computing, fault tolerance, and distributed software architecture and tools. He has published over 120 technical papers in the above areas. He has served as a member of editorial boards of several international journals, a reviewer for international journals/conference proceedings, and also as an organizing/programme committee member for many international conferences. Dr. Cao is a member of the IEEE Computer Society, the IEEE Communication Society, IEEE, and ACM. He is also a member of the IEEE Technical Committee on Distributed Processing, IEEE Technical Committee on Parallel Processing, IEEE Technical Committee on Fault Tolerant Computing, and Computer Architecture Professional Committee of the China Computer Federation. Alvin Chan is currently an assistant professor at the Hong Kong Polytechnic University. He graduated from the University of New South Wales with a Ph.D. degree in 1995 and was subsequently employed as a Research Scientist by the CSIRO, Australia. From 1997 to 1998, he was employed by the Centre for Wireless Communications, National University of Singapore as a Program Manager. Dr. Chan is one of the founding members and director of a university spin-off company, Information Access Technology Limited. He is an active consultant and has been providing consultancy services to both local and overseas companies. His research interests include mobile computing, context-aware computing and smart card applications. Yudong Sun received the B.S. and M.S. degrees from Shanghai Jiao Tong University, China. He received Ph.D. degree from the University of Hong Kong in 2002, all in computer science. From 1988 to 1996, he was among the teaching staff in Department of Computer Science and Engineering at Shanghai Jiao Tong University. From 2002 to 2003, he held a research position at the Hong Kong Polytechnic University. At present, he is a Research Associate in School of Computing Science at University of Newcastle upon Tyne, UK. His research interests include parallel and distributed computing, Web services, Grid computing, and bioinformatics. Sajal K. Das is currently a Professor of Computer Science and Engineering and the Founding Director of the Center for Research in Wireless Mobility and Networking (CReWMaN) at the University of Texas at Arlington. His current research interests include resource and mobility management in wireless networks, mobile and pervasive computing, sensor networks, mobile internet, parallel processing, and grid computing. He has published over 250 research papers, and holds four US patents in wireless mobile networks. He received the Best Paper Awards in ACM MobiCom’99, ICOIN-16, ACM, MSWiM’00 and ACM/IEEE PADS’97. Dr. Das serves on the Editorial Boards of IEEE Transactions on Mobile Computing, ACM/Kluwer Wireless Networks, Parallel Processing Letters, Journal of Parallel Algorithms and Applications. He served as General Chair of IEEE PerCom’04, IWDC’04, MASCOTS’02 ACM WoWMoM’00-02; General Vice Chair of IEEE PerCom’03, ACM MobiCom’00 and IEEE HiPC’00-01; Program Chair of IWDC’02, WoWMoM’98-99; TPC Vice Chair of ICPADS’02; and as TPC member of numerous IEEE and ACM conferences. Minyi Guo received his Ph.D. degree in information science from University of Tsukuba, Japan in 1998. From 1998 to 2000, Dr. Guo had been a research scientist of NEC Soft, Ltd. Japan. He is currently a professor at the Department of Computer Software, The University of Aizu, Japan. From 2001 to 2003, he was a visiting professor of Georgia State University, USA, Hong Kong Polytechnic University, Hong Kong. Dr. Guo has served as general chair, program committee or organizing committee chair for many international conferences, and delivered more than 20 invited talks in USA, Australia, China, and Japan. He is the editor-in-chief of the Journal of Embedded Systems. He is also in editorial board of International Journal of High Performance Computing and Networking, Journal of Embedded Computing, Journal of Parallel and Distributed Scientific and Engineering Computing, and International Journal of Computer and Applications. Dr. Guo’s research interests include parallel and distributed processing, parallelizing compilers, data parallel languages, data mining, molecular computing and software engineering. He is a member of the ACM, IEEE, IEEE Computer Society, and IEICE. He is listed in Marquis Who’s Who in Science and Engineering.     

Lower Abundance of Ammonia-Oxidizing Archaea Than Ammonia-Oxidizing Bacteria Detected in the Subsurface Sediments of the Northern South China Sea

Diversity and abundance of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in samples of the northern South China Sea subsurface sediment were assessed by analyzing the amoA gene sequences retrieved from the samples. The microbial diversity was assessed using rarefaction and phylogenetic analyses. The deep-sea subsurface sediments harbored diverse and distinct AOA and AOB communities, but the abundance of AOA was lower than that of AOB, consistent with many other studies about bacteria and archaea in subsurface sediments. Diversity of AOA shown in the OTUs and Shannon index was correlated with the concentration of nitrite in the Pearson analysis, but no obvious relationships between the diversity or abundance of AOB and the physicochemical parameters could be identified in the present study, indicating the concentration of ammonium may not be an important factor to determine the diversity and abundance of ammonia-oxidizing prokaryotes in the subsurface sediments. Additionally, Nitrosomonas-like AOB was found to be dominant in subsurface sediments of the northern South China Sea showing a different adaption strategy comparing with some Nitrosospira-like AOB lineages. Concentration of nitrite was correlated with diversity of AOA, but no correlations between diversity and abundance of AOB and the physicochemical parameters were established in the study. Supplementary materials are available for this article. Go to the publisher's online edition of Geomicrobiology Journal to view the free supplemental files.     

Store-Operated Ca2+ Channels Blockers Inhibit Lipopolysaccharide Induced Astrocyte Activation

The destruction of calcium homeostasis is an important factor leading to neurological diseases. Store-operated Ca²⁺ (SOC) channels are essential for Ca²⁺ homeostasis in many cell types. However, whether SOC channels are involved in astrocyte activation induced by lipopolysaccharide (LPS) still remains unknown. In this study, we used LPS as an exogenous stimulation to investigate the role of SOC channels in astrocyte activation. Using calcium imaging technology, we first found that SOC channels blockers, 1-[h-[3-(4-methoxyphenyl)propoxy]-4-methoxyphenethyl]-1H-imidazole (SKF-96365) and 2-aminoethyldiphenyl borate (2-APB), inhibited LPS induced [Ca²⁺]_i increase, which prompted us to speculate that SOC channels may be involved in LPS induced astrocyte activation. Further experiments confirmed our speculation shown as SOC channels blockers inhibited LPS induced astrocyte activation characterized as cell proliferation by MTS and BrdU assay, raise in glial fibrillary acidic protein expression by immunofluorescence and Western Blot and secretion of interleukin 6 (IL-6) and interleukin 1β (IL-1β) by ELISA. So, our studies showed that SOC channels are involved in LPS-induced astrocyte activation.     

Isolation and characterization of fatty acid methyl ester (FAME)‐producing Streptomyces sp. S161 from sheep (Ovis aries) faeces

An actinomycete producing oil‐like mixtures was isolated and characterized. The strain was isolated from sheep faeces and identified as Streptomyces sp. S161 based on 16S rRNA gene sequence analysis. The strain showed cellulase and xylanase activities. The ¹H nuclear magnetic resonance (NMR) spectra of the mixtures showed that the mixtures were composed of fatty acid methyl esters (52·5), triglycerides (13·7) and monoglycerides (9·1) (mol.%). Based on the gas chromatography–mass spectrometry (GC‐MS) analysis, the fatty acid methyl esters were mainly composed of C14‐C16 long‐chain fatty acids. The results indicated that Streptomyces sp. S161 could produce fatty acid methyl esters (FAME) directly from starch. To our knowledge, this is the first isolated strain that can produce biodiesel (FAME) directly from starch.

Significance and Impact of the Study

Nowadays, production of biodiesel is based on plant oils, animal fats, algal oils and microbial oils. Lipid mostly consists of triacylglycerols (TAG), and conversion of these lipids into fatty acid short‐chain alcohol esters (methanol or ethanol) is the final step in biodiesel production. In this study, an oil‐producing Streptomyces strain was isolated from sheep faeces. The oil was composed of C₁₄‐C₁₆ long‐chain fatty acid methyl esters, triglycerides and monoglycerides. This is the first isolated strain‐producing biodiesel (FAME) directly from starch. Due to showing cellulase and xylanase activities, the strain would be helpful for converting renewable lignocellulose into biodiesel directly.     

Temporal-Spatial Expressions of Spy1 in Rat Sciatic Nerve After Crush

As a novel cell cycle protein, Spy1 enhances cell proliferation, promotes the G1/S transition as well as inhibits apoptosis in response to UV irradiation. Spy1 levels are tightly regulated during mammary development, and overexpression of Spy1 accelerates tumorigenesis in vivo. But little is known about the role of Spy1 in the pathological process of damage and regeneration of the peripheral nervous system. Here we established a rat sciatic nerve crush (SNC) model to examine the spatiotemporal expression of Spy1. Spy1 expression was elevated gradually after sciatic nerve crush and peaked at day 3. The alteration was due to the increased expression of Spy1 in axons and Schwann cells after SNC. Spy1 expression correlated closely with Schwann cells proliferation in sciatic nerve post injury. Furthermore, Spy1 largely localized in axons in the crushed segment, but rarely co-localized with GAP43. These findings suggested that Spy1 participated in the pathological process response to sciatic nerve injury and may be associated with Schwann cells proliferation and axons regeneration.     

Molecular cloning, tissue expression and SNP analysis in the goat nerve growth factor gene

In this study, we cloned the full coding region of NGF gene from the caprine ovary. Result showed the caprine NGF cDNA (GenBank Accession No. JQ308184) contained a 726 bp open reading frame encoding a protein with 241 amino acid residues. Bioinformatic analysis indicated that caprine NGF amino acid sequence was 83–99 % identical to that of mouse, pig, dog, human and bovine. It was predicted that caprine NGF contained nine serine phosphorylation loci, four threonine phosphorylation loci and nine specific PKC phosphorylation loci. The NGF mRNA expression pattern showed that NGF gene was expressed highly in ovary. This work provided an important experimental basis for further research on the function of NGF in goat. A single nucleotide polymorphism (A705G) in the coding region of NGF gene was detected by PCR–RFLP and DNA sequencing in 630 goats of three breeds. The frequencies of G allele were 0.52–0.61, and frequencies of A allele were 0.48–0.39 for SN, GZ and BG breeds, respectively. The does with GG genotype had higher litter size than those with GA and AA genotypes (P < 0.05). Hence, the biochemical and physiological functions, together with the results obtained in our investigation, suggest that the NGF gene could serve as a genetic marker for litter size in goat breeding.