Which system?

Consider 4 hardware scenarios, which parallel processing architecture would suit each scenario and why?

Consider the four following Scenarios:

Scenario 1

A microcontroller used in a simple embedded system, such as a thermostat or a toy robot, needs to perform a limited set of tasks, such as reading sensor inputs and controlling actuators.

Requirements:

• Low power consumption: The embedded system is likely to be battery-powered, so the microcontroller needs to be energy efficient.
• Simple instruction set: The microcontroller needs to be able to execute a small set of basic instructions, such as arithmetic operations and data transfers.

• Low cost: The embedded system is likely to be cost-sensitive, so the microcontroller needs to be inexpensive to manufacture.

Scenario 2:

A multimedia processor used in a smartphone or tablet needs to process audio, video, and graphics data efficiently. These data types often involve applying the same operation to multiple data points, such as filtering audio samples or enhancing image pixels.

Requirements:

• High throughput: The multimedia processor needs to be able to process large amounts of data quickly to provide real-time or near-real-time performance.
• Data-level parallelism: The operations on audio, video, and graphics data can be performed independently on multiple data points, allowing for parallel execution to improve throughput.

• Instruction set optimized for media processing: The processor should include instructions specifically designed for media processing tasks, such as filtering, scaling, and compression.

Scenario 3:

A fault-tolerant system used in critical applications, such as aircraft control or medical devices, needs to be able to detect and correct errors in real-time. This can be achieved by having multiple processors execute different instructions on the same data stream and comparing the results.

Requirements:

• High availability: The system must be able to continue operating even if one or more of its components fails.
• Fault detection and correction: The system must be able to detect and correct errors in its data or processing.

• Real-time performance: The system must be able to detect and correct errors quickly enough to prevent failures.

Scenario 4:

A high-performance computing (HPC) cluster used for scientific research or big data analytics needs to perform large-scale simulations or analyze massive datasets. These tasks often involve distributing the calculations across multiple nodes in the cluster.

Requirements:

• High computational power: The cluster needs to be able to perform a large number of calculations per second to handle the complexity of scientific simulations or big data analysis.
• Scalability: The cluster should be able to accommodate additional nodes to increase its computational power as needed.
• Communication and synchronization: The nodes in the cluster need to be able to communicate and synchronise their operations to work together effectively.