Mapping Components to the Von Neumann Architecture Building Blocks
Computer architecture are the components that directly impacts program execution or system attributes that are visible to the programmer while computer organization refers to the functional components and their relationships that work together to achieve the architectural specifications. Some of the examples of architectural attributes include I/O mechanisms, number of bits used to represent different types of data, instruction set, and memory addressing techniques while examples of organizational attributes include hardware components that the programmer can see such as memory technology, computer peripherals, and control signals (Hayes, 2012).
A commercial computer system refers to any system, software, or application that has been designed for commercial purposes. They can be opensource or proprietary systems. In this paper, the focus will be on two commercial computer systems: Samsung galaxy S9 and iPhone X system. The two computer systems are mobile phones running on different platforms. Samsung galaxy s9 runs on android platform while iPhone X runs on IOS.
Von Neuman computer system is made up of three main building blocks including the central processing unit, memory, and the Input output components. The system bus connects these three components together (Simmons, Coon and Datta, 2018). Registers are the most prominent CPU items and can be directly manipulated and modified by the programs. The figure below shows the interconnections between the components of the CPU.
The following are the main components of the Neumann Model (Kami?ski, 2017):
- The memory is used for information storage such as programs or data.
- The central processing unit is used for information processing and computations.
- Input components refers to various devices that are used to enter data or issue instructions to the computer such as mouse and keyboard.
- Output component are used to give out processed information such as monitors, speakers, printers.
- Control unit ensures that every component is doing what is supposed to be doing at the right time using the correct procedures.
Each of the two computer systems have employed the von Neumann architecture.
Apple and Samsung have been battling for a very long time in the world of smartphones (Murnane, 2018). Samsung is focusing on providing the best alternatives to Apple’s iPhone that are powered by Android Operating system (Knapp, 2018). In this section, the discussion will focus on comparing iPhone X from Apple and Samsung Galaxy S9 from Samsung. The two computer systems have been compared depending on their performance, cost, and energy consumption;
In terms of performance, iPhone X is slower as compared to S9 according to an article published by Speedtest. Speed core metrics was used to compare Galaxy S9 and iPhone X which was based on user-initiated done using cellular networks. The upload and download speeds dictated the speed score and given a weight of 90%. The speeds were recorded at 10%, 50%, and 90%. The results obtained showed that Galaxy s9 had better performance as compared to iPhone X (Speedtest, 2018).
Von Neumann Model Components
Based on cost iPhone x is more expensive that Samsung Galaxy S9. For an iPhone X with 256GB the price starts at £1149 while that of 64GB starts at £999. 64GB Galaxy S9 model cost starts from £739 while that of 256GB costs £869 (ORELLANA, 2018). The prices are considerably distinguishable and more people may prefer Galaxy S9 because of better performance and prices.
Samsung galaxy s9 uses a 3000mAh battery while the iPhone X uses a 2700mAh battery (Parker, 2018). This suggests that the Galaxy S9 has more battery capacity and can store more as compared to iPhone X. If the two phones are used to do the same activities, Galaxy s9 will last 1 hour more that iPhone X. The power of the two phones lasts for a day because of the bright displays. Additionally, both phones support fast and wireless charging.
The CPU uses data path to connect the processor chips including the registers, ALU’s, and memory. The ‘gates’ control the flow of bits across the processor chips and either allow the bits to go through or not (Mano, 2013). The diagram below represents the organization of processor chips in the two computer systems.
The processor issues instructions using numeric values in the memory. One of the main tasks in designing the CPU is the engineering and programming of the instruction set. A specific numeric opcode is required by every instruction.
Cache is a high-speed static RAM that computer systems such as iPhone X and Galaxy S9 the phone microprocessor can access instead of accessing the regular RAM. It stores data and instructions that the users often access on their phones. The two computer systems have a cache memory.
The data transfer efficiency and complexity in phone multicore chips is getting more challenging and several proposals have been made by Samsung and Apple to improve communication efficiency and design flexibility in the multicore chips (Ismail, 2017). The two companies are working tirelessly to enhance this architecture to better performance and improve the overall user experience. The diagram below represents the interconnection architecture in the two systems.
The memory has two key operations: the store (value, address) for writing new values into the cell and fetch (address) for returning values without changing the value stored on the address. The two computer systems have this kind of memory which is accessed randomly allowing the CPU to access any array value sequentially at any time (Tanenbaum, 2016). The diagram below represents a typical memory management structure.
Samsung Galaxy S9 Vs iPhone X
There are two ways for mapping input/output module:
Memory mapped I/O
- Writing and reading I/O is the same as writing/ reading memory
- I/O modules are mapped to address space of the memory
- Has the capacity to use write/read instructions of a memory
Isolated I/O
- Requires special instructions for I/O like OUT and IN on 32-bit operating systems.
- Have different input/output address space.
The two computer systems have the ability to perform parallel processing. Both operating systems have evolved and have shifted from depending on instruction level parallelism (ILP). The hardware and compilers work together to implicitly exploit ILP without the knowledge of the programmer or users while task-level parallelism (TLP), data-level parallelism (DLP), and request-level parallelism (RLP) are explicitly parallel giving rise to the need to restructure applications so that it can take advantage of explicit parallelism (Orii, 2010).
For many users, especially iPhone X, this forms a major burden for them unlike in Samsung Galaxy S9 which makes easy for programmers in some instances. Samsung and Apple are adopting parallelism at several levels to enhance smartphone designs across the board however, cost and energy are still the main constraints (Weems, Kerbyson and Rajamony, 2014). The major types of parallelism that is being considered by the two computer systems are task-level parallelism (TLP) which arose because of the of the need to have tasks running and operating independently on and at the same time and data-level parallelism (DLP) which have arose because of the need to allow users to operate on the same data at the same time. Samsung and Apple are currently redesigning their hardware to take advantage of these levels of parallelism in the following four major ways (Weems, Kerbyson and Rajamony, 2011):
Graphic processing Units (GPU) makes use of DLP by employing one instruction to parallelly collect data.
Instruction-level parallelism (ILP) make use of DLP with the compiler at modest level by employing pipelining ideas and using speculative execution ideas at medium level.
Request-level parallelism (RLP) employs parallelism in tasks that are largely coupled and have been specified by the operating system or the programmer.
Thread-Level parallelism (TLP) exploits task-level parallelism or data-level parallelism in hardware model that is tightly coupled and allows parallel threads to interact.
The need to support task-level parallelism and data-level parallelism have been considered for a very long time but it’s now that they are being implemented.
Conclusion
Commercial computer system are systems that have been design for the purpose of selling to make profit or gain from them such as software, or application and can be opensource or proprietary systems. Von Neuman computer system is made up of three main building blocks including the central processing unit, memory, and the Input output components. Its main components include: the memory is used for information storage such as programs or data, central processing unit is used for information processing and computations, input components refers to various devices that are used to enter data or issue instructions to the computer such as mouse and keyboard, output component are used to give out processed information such as monitors, speakers, printers, and control unit ensures that every component is doing what is supposed to be doing at the right time using the correct procedures.
Performance
Operating systems are responsible for handling errors, computer security, and multitasking to allow users to execute many application software at the same time. Determining the performance of Samsung Galaxy S9 and iPhone X is a hard task but one way to determine this was to run similar task on both phones and determine how long it takes to execute and process. It is easy to customize a Galaxy S9 and tune it to meet your preferences as compared to iPhone X.
The processor issues instructions using numeric values in the memory. One of the main tasks in designing the CPU is the engineering and programming of the instruction set. For many users, especially iPhone X, this forms a major burden for them unlike in Samsung Galaxy S9 which makes easy for programmers in some instances. Samsung and Apple are adopting parallelism at several levels to enhances computer designs across the board however, cost and energy are still the main constraints. The major types of parallelism that is being considered by the two computer systems are task-level parallelism (TLP) which arose because of the of the need to have tasks running and operating independently on and at the same time and data-level parallelism (DLP) which have arose because of the need to allow users to operate on the same data at the same time.
Reference List
Aston, V. (2018). Architecture of a Smartphone and SOC(system on chip). [online] Top5stuffs.blogspot.com. Available at: https://top5stuffs.blogspot.com/2014/09/architecture-of-smartphone-and.html [Accessed 25 Nov. 2018].
Hayes, J. (2012). Computer architecture and organization. New York: McGraw-Hill Primis Custom.
Ismail, N. (2017). Interconnection Oriented Architecture: the changing role of the data centre. [online] Information Age. Available at: https://www.information-age.com/interconnection-oriented-architecture-changing-role-data-centre-123464094/ [Accessed 25 Nov. 2018].
Kami?ski, K. (2017). The Weyl–von Neumann theorem in von Neumann factors. Journal of Applied Analysis, 23(1).
Knapp, M. (2018). iPhone XS vs Samsung Galaxy S9. [online] TechRadar. Available at: https://www.techradar.com/news/iphone-xs-vs-galaxy-s9 [Accessed 25 Nov. 2018].
Mano, M. (2013). Computer system architecture. New Delhi: Prentice-Hall of India.
Margaret, R. (2018). What is cache memory? – Definition from WhatIs.com. [online] SearchStorage. Available at: https://searchstorage.techtarget.com/definition/cache-memory [Accessed 25 Nov. 2018].
Murnane, K. (2018). Which Is Faster, The iPhone X or the Galaxy S9?. [online] Forbes. Available at: https://www.forbes.com/sites/kevinmurnane/2018/07/23/which-is-faster-the-iphone-x-or-the-galaxy-s9/#7a426f52a55e [Accessed 25 Nov. 2018].
ORELLANA, V. (2018). Choose between the Galaxy S9 and the iPhone X. [online] CNET. Available at: https://www.cnet.com/news/iphone-x-vs-galaxy-s9-which-is-best/ [Accessed 25 Nov. 2018].
Orii, S. (2010). Metrics for evaluation of parallel efficiency toward highly parallel processing. Parallel Computing, 36(1), pp.16-25.
Parker, M. (2018). Samsung Galaxy S9 vs iPhone X: Which should you pick?. [online] Trusted Reviews. Available at: https://www.trustedreviews.com/news/galaxy-s9-vs-iphone-x-3402202 [Accessed 25 Nov. 2018].
Simmons, D., Coon, J. and Datta, A. (2018). The von Neumann Theil index: characterizing graph centralization using the von Neumann index. Journal of Complex Networks.
Speedtest, S. (2018). 2018 Speedtest U.S. Mobile Performance Report by Ookla. [online] Speedtest.net. Available at: https://www.speedtest.net/reports/united-states/#mobile [Accessed 25 Nov. 2018].
Tanenbaum, A. (2016). Structured Computer Organization. Pearson India.
Weems, C., Kerbyson, D. And Rajamony, R. (2011). Guest Editor’s Note: Large-Scale Parallel Processing. Parallel Processing Letters, 21(03), Pp.275-277.
Weems, C., Kerbyson, D. and Rajamony, R. (2014). Guest Editors’ Note: Special Issue on Large-Scale Parallel Processing. Parallel Processing Letters, 24(04), p.1402003.
Wyld, D., Zizka, J. and Nagamalai, D. (2012). Advances in computer science, engineering & applications. Berlin: Springer.
Order an Essay Now & Get These Features For Free:
Turnitin Report
Formatting
Title Page
Citation
Outline
