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Simulating the efficiency of business processes could reveal crucial bottlenecks for manufacturing companies and could lead to significant optimizations resulting in decreased time to market, more efficient resource utilization, and larger profit. While such business optimization software is widely utilized by larger companies, SMEs typically do not have the required expertise and resources to efficiently exploit these advantages. The aim of this work is to explore how simulation software vendors and consultancies can extend their portfolio to SMEs by providing business process optimization based on a cloud computing platform. By executing simulation runs on the cloud, software vendors and associated business consultancies can get access to large computing power and data storage capacity on demand, run large simulation scenarios on behalf of their clients, analyze simulation results, and advise their clients regarding process optimization. The solution is mutually beneficial for both vendor/consultant and the end-user SME. End-user companies will only pay for the service without requiring large upfront costs for software licenses and expensive hardware. Software vendors can extend their business towards the SME market with potentially huge benefits.

In this paper, we present a revised version of BilKristal 3.0 tool. Raycast screenshot functionality is added to provide improved visual analysis. We added atomic distance analysis functionality to assess crystalline defects. We improved visualization capabilities by adding high level cut function definitions. Discovered bugs are fixed and small performance optimizations are made. New version program summary Program title: BilKristal 4.0 Catalogue identifier: ADYU_v4_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ADYU_v4_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 370130 No. of bytes in distributed program, including test data, etc.: 8350850 Distribution format: tar.gz Programming language: C, C++, Microsoft .NET Framework 2.0 and OpenGL Libraries. Computer: Personal Computers with Windows operating system. Operating system: Windows XP or higher. RAM: 20–60 Megabytes. Classification: 8. External routines: Microsoft .NET Framework 2.0. For the visualization tool, graphics card driver should also support OpenGL. Catalogue identifier of previous version: ADYU_v3_0 Journal reference of previous version: Comput. Phys. Comm. 187 (2015) 266 Does the new version supersede the previous version?: Yes Nature of problem: Determining the crystal structure parameters of a material is a very important issue in crystallography. Knowing the crystal structure parameters helps the understanding of the physical behavior of material. For complex structures, particularly for materials which also contain local symmetry as well as global symmetry, obtaining crystal parameters can be very hard. Solution method: The tool extracts crystal parameters such as primitive vectors, basis vectors and identifies the space group from atomic coordinates of crystal structures. Reasons for new version: Additional features, Performance optimizations, Minor bug corrections. Summary of revisions: • Raycast screenshot functionality is added to the visualization tool. A raycasting algorithm similar to the one described in [4, 6] is used. The algorithm is multi-core parallelized as described in [5]. • Atomic distance analysis functionality is added. Tool can analyze the crystal structure and give statistical information of atom to atom distances. • In the visualization tool, high level cut function support is added. Users can define cut functions, not just as cut-planes but with more complex functions as well. • Automatic primitive vector and basis vector selection options are added. This way the system selects the simplest primitive and basis vector alternatives and continues without interrupting the user. • In the visualization tool, an unused log file was being created and a redundant configuration file was being used. These issues are corrected. • Dead-codes are removed to improve clarity. Restrictions: Assumptions are explained in [1, 2, 3]. However, none of them can be considered as a restriction to the complexity of the problem. Running time: The tool was able to process input files with more than a million atoms in less than 20 seconds on a PC with an Athlon quad-core CPU at 3.2 GHz using the default parameter values. References: [1] Erhan Okuyan, Ugur Gudukbay, and Oguz Gulseren, Pattern Information Extraction from Crystal Structures, Computer Physics Communications 176 (2007) 486. [2] Erhan Okuyan and Ugur Gudukbay, BilKristal 2.0: A Tool for Pattern Information Extraction from Crystal Structures, Computer Physics Communications 185 (2014) 442. [3] Erhan Okuyan and Erkan Okuyan, A Tool for Pattern Information Extraction and Defect Quantification from Crystal Structures, Computer Physics Communications 187 (2015) 266. [4] Erhan Okuyan, Ugur Gudukbay and Veysi Isler, Dynamic view-dependent visualization of unstructured tetrahedral volumetric meshes, Journal of Visualization 15-2 (2012) 167–178. [5] Erhan Okuyan and Ugur Gudukbay, Direct Volume Rendering of Unstructured Tetrahedral Meshes using CUDA and OpenMP, Journal of Supercomputing 67-2 (2014) 324–344. [6] Erhan Okuyan, Ugur Gudukbay, Ceyhun Bulutay, and Karl-Heinz Heinig, MaterialVis: Material Visualization Tool using Direct Volume and Surface Rendering Techniques, Journal of Molecular Graphics and Modelling 50 (2014) 50–60.