Multicore development environment for embedded processor in arduino IDE

Internet of things (IoT) technology has found more applications that require complex computation while still preserving power. Embedded processors as the core of the IoT system approaches the need for computation by employing a parallel processor system, namely MPSoC. While various MPSoCs hardware is widely available, there is limited software support form of user-friendly libraries and development platform. There is a need for such a platform to facilitate both the study and development of parallel embedded software. arduino as the widely used embedded development platform is yet to officially support multicore programming. This work proposes an arduino-based development environment that supports multicore programming while maintaining arduino’s simple program structure, targeted at specific low-power MPSoC, the RUMPS401. The environment is fully functional, and while it targets only specific MPSoC, the proposed environment can easily be adopted to other MPSoCs with similar structures with minimal modification

MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools, a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments

ParaMonte: An Efficient Serial/Parallel MCMC Library

The scientific inference is a multistep process requiring observational data from which a model/hypothesis is derived. The parameters of this physical model then have to be tuned to more accurately represent data in a process known as model calibration. This calibrated model is then validated and is finally used to predict different quantities of interest. The most fundamental tool for model calibration and uncertainty quantification is the Markov Chain Monte Carlo (MCMC). While existing packages achieve many of the goals of the MCMC simulations, none currently addresses all critical aspects of an MCMC simulation. For instance, packages are frequently limited to only one programming language environment, perform serial or parallel simulations, or lack restart functionality. We present ParaMonte, a generic user-friendly, high- performance Monte Carlo simulation toolbox for serial and parallel Monte Carlo simulations accessible from multiple programming languages. ParaMonte features automatically-enabled restart functionality of all simulations in serial or parallel and comprehensive post-processing and visualization of the simulation results. This package is available to the public under the MIT license from its permanent repository: https://github.com/cdslaborg/paramont

Multicore development environment for embedded processor in arduino IDE

Internet of things (IoT) technology has found more applications that require complex computation while still preserving power. Embedded processors as the core of the IoT system approaches the need for computation by employing a parallel processor system, namely MPSoC. While various MPSoCs hardware is widely available, there is limited software support form of user-friendly libraries and development platform. There is a need for such a platform to facilitate both the study and development of parallel embedded software. arduino as the widely used embedded development platform is yet to officially support multicore programming. This work proposes an arduino-based development environment that supports multicore programming while maintaining arduino’s simple program structure, targeted at specific low-power MPSoC, the RUMPS401. The environment is fully functional, and while it targets only specific MPSoC, the proposed environment can easily be adopted to other MPSoCs with similar structures with minimal modification

Ergonomic design improvement at Koko Minda Food Industries (M) Sdn. Bhd

Koko Minda Food Industries (M) Sdn. Bhd was founded and established on year 2010 and still operating until now. This company is founded by Mr. Salim bin Salleh after he retired from working with government on year 2009. He decided to open up Koko Minda Food Industries (M) Sdn. Bhd because he has desired to continue working after being retired from working due to his sickness. His daughter, Ms. Nurul Firdaus binti Salim also giving hands to help him and serve as the Director of Administration & Marketing to run Koko Minda Food Industries (M) Sdn. Bhd. This company is located at IKS Halal Hub Serkam, Merlimau, Malacca, Malaysia and will be relocated to a new factory which 200 meters from its current factory

Evoplex: A platform for agent-based modeling on networks

Agent-based modeling and network science have been used extensively to advance our understanding of emergent collective behavior in systems that are composed of a large number of simple interacting individuals or agents. With the increasing availability of high computational power in affordable personal computers, dedicated efforts to develop multi-threaded, scalable and easy-to-use software for agent-based simulations are needed more than ever. Evoplex meets this need by providing a fast, robust and extensible platform for developing agent-based models and multi-agent systems on networks. Each agent is represented as a node and interacts with its neighbors, as defined by the network structure. Evoplex is ideal for modeling complex systems, for example in evolutionary game theory and computational social science. In Evoplex, the models are not coupled to the execution parameters or the visualization tools, and there is a user-friendly graphical interface which makes it easy for all users, ranging from newcomers to experienced, to create, analyze, replicate and reproduce the experiments.Comment: 6 pages, 5 figures; accepted for publication in SoftwareX [software available at https://evoplex.org