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Questions and Answers
What does High Performance Computing (HPC) typically aggregate to deliver higher performance?
What does High Performance Computing (HPC) typically aggregate to deliver higher performance?
What primarily drives the need for greater computing power in HPC?
What primarily drives the need for greater computing power in HPC?
Which of the following application areas utilizes HPC for complex simulations?
Which of the following application areas utilizes HPC for complex simulations?
Why are single-core processors not sufficient for the simulations required in HPC?
Why are single-core processors not sufficient for the simulations required in HPC?
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What is one of the key areas that Dr. Maha Dessokey specializes in?
What is one of the key areas that Dr. Maha Dessokey specializes in?
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What characterizes the MIMD architecture in terms of parallelism?
What characterizes the MIMD architecture in terms of parallelism?
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Which category of Flynn's taxonomy allows for executing a single instruction on many data items simultaneously?
Which category of Flynn's taxonomy allows for executing a single instruction on many data items simultaneously?
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What form of parallelism is primarily exemplified by pipelining?
What form of parallelism is primarily exemplified by pipelining?
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In Flynn's taxonomy, which architecture represents a uniprocessor model?
In Flynn's taxonomy, which architecture represents a uniprocessor model?
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What type of parallelism allows independent modules of a program to execute simultaneously?
What type of parallelism allows independent modules of a program to execute simultaneously?
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What is the main advantage of parallel computing over serial computing?
What is the main advantage of parallel computing over serial computing?
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Which of the following areas does NOT apply high-performance computing (HPC)?
Which of the following areas does NOT apply high-performance computing (HPC)?
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What challenge is associated with creating faster processors?
What challenge is associated with creating faster processors?
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In which field is parallel computing especially beneficial for real-time applications?
In which field is parallel computing especially beneficial for real-time applications?
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Which of the following best describes a key application area for HPC in Earth Science?
Which of the following best describes a key application area for HPC in Earth Science?
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What is a significant requirement for handling increased complexity in multimedia?
What is a significant requirement for handling increased complexity in multimedia?
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Which of the following applications is related to nuclear science in the context of HPC?
Which of the following applications is related to nuclear science in the context of HPC?
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Which of the following applications of HPC relates directly to the field of aerodynamics?
Which of the following applications of HPC relates directly to the field of aerodynamics?
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Study Notes
High Performance Computing (HPC)
- HPC refers to aggregating computing power to solve complex problems in science, engineering, or business.
- HPC delivers much higher performance than typical desktop computers or workstations.
Key Drivers of HPC
- Growth in data generation.
- Need for complex simulations and modeling to solve problems in fields like climate science, physics, and bioinformatics.
- Single-core processors are not powerful enough for the simulations needed.
- Making processors with faster clock speeds is difficult due to cost, power, and heat limitations.
- Expensive to put huge memory on a single processor.
Serial Computing
- Only one instruction may execute at any given time.
Parallel Computing
- Parallel computing refers to a form of computation in which many calculations are carried out concurrently, allowing large problems to be divided into smaller ones that are solved simultaneously.
HPC Applications
- Space Science: Astrophysics and Astronomy.
- Earth Science: Understanding geological structures, water resource modelling, seismic exploration.
- Atmospheric Science: Climate and weather forecasting, air quality.
- Life Science: Drug designing, genome sequencing, protein folding.
- Nuclear Science: Nuclear power, Nuclear medicine (cancer), defense.
- Nano Science: Semiconductor physics, microfabrication, molecular biology, exploration of new materials.
- Crash Simulation: Automobile and mechanical engineering.
- Aerodynamics Simulation & Aircraft Designing: Aeronautics and mechanical engineering.
- Structural Analysis: Civil engineering and architecture.
- Multimedia and Animation: High-resolution content (4K, 8K), advanced visual effects (VFX), real-time rendering, simulations for gaming and virtual reality (VR) applications, large data processing.
Parallel Processing
- A form of computation where many calculations are performed concurrently.
Von Neumann Architecture Model
- Consists of a stored-program and data in a memory unit.
- Instructions are fetched, decoded, data is retrieved, executed, and results are stored back.
Flynn's Classical Taxonomy
- A model based on where parallelism originates: data or instructions.
- Divides architectures into categories based on single or multiple streams of instructions and data.
SISD (Single Instruction, Single Data)
- Uniprocessor architecture, sequential processing.
SIMD (Single Instruction, Multiple Data)
- Parallelism from data (same instruction, multiple data points).
MISD (Multiple Instruction, Single Data)
- Systolic array and pipeline-like architectures.
MIMD (Multiple Instruction, Multiple Data)
- Parallelism from both instruction and data streams.
- Sub-categories:
- Shared memory: Multiple processors share a common memory.
- Distributed memory: Each processor has its own private memory.
Pipelining
- A technique that breaks a task into stages and allows multiple tasks to be processed concurrently, improving execution speed.
Types of Parallelism
- Data parallelism: Many data items processed in the same way simultaneously.
- Functional parallelism: Program with independent modules executed concurrently.
- Overlapped/ Temporal Parallelism: Tasks executed in a sequential order, with overlapping execution.
- Pipelining: Most important form of overlapped parallelism.
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Description
This quiz covers the fundamental concepts of High Performance Computing (HPC) including its drivers, applications, and the difference between serial and parallel computing. Explore the impact of data generation and the limitations of traditional computing in solving complex scientific problems.
