ITSU1001 Introduction to Computer Systems and Networking Assignment Sample

Introduction

PC Workstation is used by the organization for the maintenance of large and complicated tasks. It is capable of handling the mass load of the computers and other devices that are connected within the scope of the network. In this paper, the proposal of the system configuration will be done for the organization named ThingXthings Tech Private Limited. The configuration with the system maintenance will be proposed in this scenario along with the costing of the components. The system that will be referred in this paper will be of high configuration because the system is using the Machine Learning system with the application of AI which requires multiple GPU to work with[1]. Thus, a suitable configuration will be discussed which can perform the desired tasks for the organization efficiently.

Industry Background

There are different industries there who deal with the AI system using the PC Work stations. This case can be widely applicable in the case of the online gaming system and trading system. The purpose of the operation of the organization is to maintain the websites of different other companies with the application of Machine learning[2]. In such an industry, the websites of those companies receive huge traffics and those are utilized for the recommender and analytical purposes. This requires the speedy processor and the highly effective underlying technology which can perform those task in real-time and within a fraction of time. ThingXthings is one such organization that performs those tasks. Thus, they are recommended to use the OC workstation with a high configuration which will be capable of monitoring all the issues. Thus, the ultimate purpose of the PC Workstation is to apply Machine learning with the help of Artificial Intelligence for effective control over the websites. The recommended configuration of the PC Workstation is the single CPU and multi GPU or the implication of fast deployment of the workloads using the Deep Learning Mechanism[3].

System Requirement

The system of the ThingXthings will be high-end with the processor of multi-functionalities and with the capability of parallel computing. The requirements and the component overviews are discussed below:

GPU: For a PC Workstation which will deal with the multi-processing, should have the high-end Graphics Processing unit. This is used for the high-speed processing of the 2-D and 3-D graphics and also for the 3-D graphics rendering purpose[4]. However, the GPU is chosen for the system is 4 RTX 2080Ti.

Processor: The processor of this system drives the general-purpose works like the driving of the mechanisms and to control over the ports for data transactions. This is the separate unit of the GPU and has a separate set of works there. The cosen processor for this system is Intel Xeon-W 2195 18-core. This is an 18-core processor that acts fast in this scenario and hence will increase the efficiency of the operations[5].

RAM: Random Access Memory plays an important role in accessing and controlling the websites and relevant data. As there are multiple applications will be running and the sufficient memories are required to keep all those applications alive, the high capacity Random Access Memory like 256GB memory is required where the huge number of data can be stored to run all those applications[6].

Storage: The system requires storage memory to keep the data and to backup it for future purposes. The storages are chosen in this context are:

1. 1TB system SSD

2. 2TB data SSD

3. 4GB storage HD

Motherboard: Motherboard is the embedded system where all the processors and the GPU are attached. As the ThingXthings is controlling multiple websites and the traffic load simultaneously, thus the high configuration of the motherboard is chosen for effective and fast operation[2]. The motherboard is chosen for the purpose has the features like 4 Full X16, PLX switched and metal reinforced PCIe slots

Chassis: As the motherboard containing the high-speed processor and Graphics Processing unit, it becomes very hot within some times. Thus, the cooling operation and mechanism should be in the motherboard so that the semiconductor devices will not be damaged for over-heating[6]. Thus the optimal chassis with excellent cooling is chosen to protect the motherboard and other devices.

Review of Configurations

There are different configurations for such PC Workstation that are available in the market and those are widely used in a different system to control and monitor the servers and multiple systems. Three out of those systems will be reviewed in this section along with the discussion of the advantages and disadvantages of those.

So, among these three systems, the preferable one is the PHEIDOLE X820X which satisfies the requirements for the system of ThingXthings and this will be used for the proposal of the system configuration[3].

Detailed Chosen System Configuration with Cost

The system that is specified in the earlier section will be chosen as the proposed system with its different good features and advantages[4]. The system is also chosen for the purpose that it is satisfying the requirements and within the budget where the calculated budget is 10000 USD. The system configuration with the partial breakdown of cost is shown below:

So, from the BOM, it can e seen that the estimated cost of the components and services is about 7000 USD which is below the budget and the components are obtained with the required functionality.

System Installation Guidelines and Safety Procedures

The system can be available in the ready form in the market. Though there are some cautions to be taken while at the time of installation to maintain the safety of the new and existing system[2]. The guidelines are:

1. Check for the Voltage and Current in the AC Mains.

2. Ensure the parts of the workstations are connected successfully.

3. Ensure the troubleshooting is done properly and the testing is done.

Project Schedule – Timeline for The Completion of This Project

The project schedule will be discussed in this section and will be shown in the form of Gantt Chart as follows:

System Maintenance Tasks

System maintenance is an important part of the Network and the system configuration. After the deployment of the system, the maintenance will be done as per the schedules. System maintenance tasks are shown below[1]:

Daily: Checking the System connection, Internet connection, the connection of the devices

Weekly: Checking for the OS and System updates, Check for the system upgrade and available patches, Checking the operation of the Firewalls.

Conclusion

In this paper, the system configuration is proposed for the organization named ThingXthings. In this context, the research is done for the available system configurations, and from those, the best configuration is chosen concerning to the factor and the applications. After choosing the optimum configuration, the cost breakdown is calculated. As the system is proposed to ThingXthings, the project timelines are discussed and the maintenance schedules are proposed. After watching the system configuration and the budget, it can be said that if the budget will be higher, more effective workstations will be available.

References

[1] V. C. Reis, M. F. Santos, M. J. Carmo and F. C. Ferreira, “Control of level systems by arduino via PC platform,” 20th International Conference on System Theory, Control and Computing (ICSTCC), 2016.

[2] P. Gaj, M. Skrzewski, J. Stój and J. Flak, “Virtualization as a Way to Distribute PC-Based Functionalities,” IEEE Transactions on Industrial Informatics, vol. 11, no. 3, pp. 763 - 770, 2015.

[3] A. Dziekonski, P. Sypek, A. Lamecki and M. Mrozowski, “Communication and Load Balancing Optimization for Finite Element Electromagnetic Simulations Using Multi-GPU Workstation,” IEEE Transactions on Microwave Theory and Techniques, vol. 65, no. 8, 2017.

[4] X. Zhang, L. Wang and Y. Chen, “Multi-Objective Optimization for Multi-Line and U-Shape Layout of Sewing Assembly Line in Apparel Industry,” IEEE Access, vol. 7, 2019.

[5] H. G. Gürbüz and B. Tekinerdogan, “Software Metrics for Green Parallel Computing of Big Data Systems,” IEEE International Congress on Big Data (BigData Congress), 2016.

[6] X. Wang and X. Jin, “A fast parallel large-scale grid generator for parallel computing in engineering simulation,” IEEE International Conference of Online Analysis and Computing Science (ICOACS), 2016.

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