Integrating multiple clusters for compute-intensive applications

Multicluster grids provide one promising solution to satisfying the growing computational demands of compute-intensive applications. However, it is challenging to seamlessly integrate all participating clusters in different domains into a single virtual computational platform. In order to fully utilize the capabilities of multicluster grids, computer scientists need to deal with the issue of joining together participating autonomic systems practically and efficiently to execute grid-enabled applications. Driven by several compute-intensive applications, this theses develops a multicluster grid management toolkit called Pelecanus to bridge the gap between user\u27s needs and the system\u27s heterogeneity. Application scientists will be able to conduct very large-scale execution across multiclusters with transparent QoS assurance. A novel model called DA-TC (Dynamic Assignment with Task Containers) is developed and is integrated into Pelecanus. This model uses the concept of a task container that allows one to decouple resource allocation from resource binding. It employs static load balancing for task container distribution and dynamic load balancing for task assignment. The slowest resources become useful rather than be bottlenecks in this manner. A cluster abstraction is implemented, which not only provides various cluster information for the DA-TC execution model, but also can be used as a standalone toolkit to monitor and evaluate the clusters\u27 functionality and performance. The performance of the proposed DA-TC model is evaluated both theoretically and experimentally. Results demonstrate the importance of reducing queuing time in decreasing the total turnaround time for an application. Experiments were conducted to understand the performance of various aspects of the DA-TC model. Experiments showed that our model could significantly reduce turnaround time and increase resource utilization for our targeted application scenarios. Four applications are implemented as case studies to determine the applicability of the DA-TC model. In each case the turnaround time is greatly reduced, which demonstrates that the DA-TC model is efficient for assisting application scientists in conducting their research. In addition, virtual resources were integrated into the DA-TC model for application execution. Experiments show that the execution model proposed in this thesis can work seamlessly with multiple hybrid grid/cloud resources to achieve reduced turnaround time

Parallel Tempering Simulation of the three-dimensional Edwards-Anderson Model with Compact Asynchronous Multispin Coding on GPU

Monte Carlo simulations of the Ising model play an important role in the field of computational statistical physics, and they have revealed many properties of the model over the past few decades. However, the effect of frustration due to random disorder, in particular the possible spin glass phase, remains a crucial but poorly understood problem. One of the obstacles in the Monte Carlo simulation of random frustrated systems is their long relaxation time making an efficient parallel implementation on state-of-the-art computation platforms highly desirable. The Graphics Processing Unit (GPU) is such a platform that provides an opportunity to significantly enhance the computational performance and thus gain new insight into this problem. In this paper, we present optimization and tuning approaches for the CUDA implementation of the spin glass simulation on GPUs. We discuss the integration of various design alternatives, such as GPU kernel construction with minimal communication, memory tiling, and look-up tables. We present a binary data format, Compact Asynchronous Multispin Coding (CAMSC), which provides an additional $28.4\%$ speedup compared with the traditionally used Asynchronous Multispin Coding (AMSC). Our overall design sustains a performance of 33.5 picoseconds per spin flip attempt for simulating the three-dimensional Edwards-Anderson model with parallel tempering, which significantly improves the performance over existing GPU implementations.Comment: 15 pages, 18 figure

Fastened CROWN: Tightened Neural Network Robustness Certificates

The rapid growth of deep learning applications in real life is accompanied by severe safety concerns. To mitigate this uneasy phenomenon, much research has been done providing reliable evaluations of the fragility level in different deep neural networks. Apart from devising adversarial attacks, quantifiers that certify safeguarded regions have also been designed in the past five years. The summarizing work of Salman et al. unifies a family of existing verifiers under a convex relaxation framework. We draw inspiration from such work and further demonstrate the optimality of deterministic CROWN (Zhang et al. 2018) solutions in a given linear programming problem under mild constraints. Given this theoretical result, the computationally expensive linear programming based method is shown to be unnecessary. We then propose an optimization-based approach \textit{FROWN} (\textbf{F}astened C\textbf{ROWN}): a general algorithm to tighten robustness certificates for neural networks. Extensive experiments on various networks trained individually verify the effectiveness of FROWN in safeguarding larger robust regions.Comment: Zhaoyang Lyu and Ching-Yun Ko contributed equally, accepted to AAAI 202

Problem-based learning module of organic insecticide for the aborigine students in Malaysia

Problem-based learning (PBL) is a teaching model that uses real-world problems to lead students toward the learning objective of a course. It has been widely adopted in Malaysian education. However, PBL module for aboriginal people is scarce. This study aimed to provide suitable PBL activities in learning environmental problems by developing a PBL teaching module for the aborigine community and accessing its suitability. In this study, data was collected through an online validation form that was given to four validators, all of them have science or chemistry education backgrounds. The online questionnaires collected were further analyzed to investigate their responses to the module. The result has shown positive feedback (95.83%) as the responses are very encouraging. All respondents give approbation to the objectives of the module which are clearly stated and are parallel with the content. Many of them also strongly agree that the PBL model and the language used are suitable in this module. There is no doubt that PBL is a valuable tool to teach chemistry to improve students’ critical thinking and problem-solving skills effectively

Compiling a High-Level Directive-Based Programming Model for GPGPUs,

Abstract. OpenACC is an emerging directive-based programming model for programming accelerators that typically enable non-expert programmers to achieve portable and productive performance of their applications. In this paper, we present the research and development challenges, and our solutions to create an open-source OpenACC compiler in a main stream compiler framework (OpenUH of a branch of Open64). We discuss in details our loop mapping techniques, i.e. how to distribute loop iterations over the GPGPU's threading architectures, as well as their impacts on performance. The runtime support of this programming model are also presented. The compiler was evaluated with several commonly used benchmarks, and delivered similar performance to those obtained using a commercial compiler. We hope this implementation to serve as compiler infrastructure for researchers to explore advanced compiler techniques, to extend OpenACC to other programming languages, or to build performance tools used with OpenACC programs

New Insights Into the Role of Follicle-Stimulating Hormone in Sex Differentiation of the Protogynous Orange-Spotted Grouper, Epinephelus coioides

Follicle-stimulating hormone (FSH) signaling is considered to be essential for early gametogenesis in teleosts, but its functional roles during sex differentiation are largely unknown. In this study, we investigated the effects of long-term and short-term FSH injection on sex differentiation in the protogynous orange-spotted grouper (Epinephelus coioides). Long-term FSH treatment initially promoted the formation of ovaries but subsequently induced a male fate. The expression of female pathway genes was initially increased but then decreased, whereas the expression of male pathway genes was up-regulated only during long-term FSH treatment. The genes related to the synthesis of sex steroid hormones, as well as serum 11-ketotestosterone and estradiol, were also up-regulated during long-term FSH treatment. Short-term FSH treatment activated genes in the female pathway (especially cyp19a1a) at low doses but caused inhibition at high doses. Genes in the male pathway were up-regulated by high concentrations of FSH over the short term. Finally, we found that low, but not high, concentrations of FSH treatment activated cyp19a1a promoter activities in human embryonic kidney (HEK) 293 cells. Overall, our data suggested that FSH may induce ovarian differentiation or a change to a male sex fate in the protogynous orange-spotted grouper, and that these processes occurred in an FSH concentration-dependent manner

Algorithmic Verification of Intransitive Noninterference for 3-domain Security Policies with a SAT Solver

Abstract: In this paper we propose an automated verification approach to checking intransitive noninterference for deterministic finite state systems. Our approach is based on the counterexamples search verification strategy, and is conducted in gradual manner. It produces counterexamples of minimal length. Further, we reduce the counterexamples search to propositional satisfiability. For the case that there are no counterexamples, we also introduce the window induction proof method in order to avoid considering unnecessary iterations, and show that the induction proof can be performed by the boolean decision procedure. In addition, based on graph-theoretic properties of systems we propose an over-approximation to the length of the smallest counterexample, and the over-approximation can also be checked by the boolean decision procedure

Having a Same Type IIS Enzyme’s Restriction Site on Guide RNA Sequence Does Not Affect Golden Gate (GG) Cloning and Subsequent CRISPR/Cas Mutagenesis

Golden gate/modular cloning facilitates faster and more efficient cloning by utilizing the unique features of the type IIS restriction enzymes. However, it is known that targeted insertion of DNA fragment(s) must not include internal type IIS restriction recognition sites. In the case of cloning CRISPR constructs by using golden gate (GG) cloning, this narrows down the scope of guide RNA (gRNA) picks because the selection of a good gRNA for successful genome editing requires some obligation of fulfillment, and it is unwanted if a good gRNA candidate cannot be picked only because it has an internal type IIS restriction recognition site. In this article, we have shown that the presence of a type IIS restriction recognition site in a gRNA does not affect cloning and subsequent genome editing. After each step of GG reactions, correct insertions of gRNAs were verified by colony color and restriction digestion and were further confirmed by sequencing. Finally, the final vector containing a Cas12a nuclease and four gRNAs was used for Agrobacterium-mediated citrus cell transformation. Sequencing of PCR amplicons flanking gRNA-2 showed a substitution (C to T) mutation in transgenic plants. The knowledge derived from this study could widen the scope of GG cloning, particularly of gRNAs selection for GG-mediated cloning into CRISPR vectors

Algorithmic Verification of Intransitive Noninterference for 3-domain Security Policies with a SAT Solver

In this paper we propose an automated verification approach to checking intransitive noninterference for deterministic finite state systems. Our approach is based on the counterexamples search verification strategy, and is conducted in gradual manner. It produces counterexamples of minimal length. Further, we reduce the counterexamples search to propositional satisfiability. For the case that there are no counterexamples, we also introduce the window induction proof method in order to avoid considering unnecessary iterations, and show that the induction proof can be performed by the boolean decision procedure. In addition, based on graph-theoretic properties of systems we propose an over-approximation to the length of the smallest counterexample, and the over-approximation can also be checked by the boolean decision procedure