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Questions and Answers
What is a key disadvantage of Single Instruction Single Data (SISD) systems?
What is a key disadvantage of Single Instruction Single Data (SISD) systems?
Which of the following describes Single Instruction Multiple Data (SIMD) systems?
Which of the following describes Single Instruction Multiple Data (SIMD) systems?
What is a common application of SIMD technology?
What is a common application of SIMD technology?
Which statement about MISD architecture is true?
Which statement about MISD architecture is true?
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What is one of the primary advantages of using SIMD systems?
What is one of the primary advantages of using SIMD systems?
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Which of the following statements is correct regarding SISD systems?
Which of the following statements is correct regarding SISD systems?
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What does the term 'pipelining' refer to in parallel processing architectures?
What does the term 'pipelining' refer to in parallel processing architectures?
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How long does pipelined laundry take to complete?
How long does pipelined laundry take to complete?
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Which stage in the pipelined laundry process has the longest duration?
Which stage in the pipelined laundry process has the longest duration?
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What determines the finish time of the entire laundry task in a pipeline?
What determines the finish time of the entire laundry task in a pipeline?
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What is a key feature of pipelined laundry compared to sequential laundry?
What is a key feature of pipelined laundry compared to sequential laundry?
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What does pipelining in laundry execution primarily illustrate?
What does pipelining in laundry execution primarily illustrate?
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How does the execution time of an individual task in pipelined laundry compare to its total sequential time?
How does the execution time of an individual task in pipelined laundry compare to its total sequential time?
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Which of the following statements is true regarding task order in pipelined execution?
Which of the following statements is true regarding task order in pipelined execution?
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What is the significance of parallel execution in pipelined laundry?
What is the significance of parallel execution in pipelined laundry?
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What is the average task execution time of the pipelined laundry, given it totals 3.5 hours for 4 tasks?
What is the average task execution time of the pipelined laundry, given it totals 3.5 hours for 4 tasks?
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What is the total time required to complete n tasks in a k-segment pipeline?
What is the total time required to complete n tasks in a k-segment pipeline?
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When will the first task T1 be completed in a k-segment pipeline?
When will the first task T1 be completed in a k-segment pipeline?
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What does the speedup of a pipeline processing over a non-pipeline processing depend on?
What does the speedup of a pipeline processing over a non-pipeline processing depend on?
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In the context of pipeline processing, what happens once the pipeline is full?
In the context of pipeline processing, what happens once the pipeline is full?
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What is the theoretical maximum speedup that a pipeline can provide based on the number of segments?
What is the theoretical maximum speedup that a pipeline can provide based on the number of segments?
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What is illustrated by the example of laundry in the context of pipelining?
What is illustrated by the example of laundry in the context of pipelining?
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What defines a balanced pipeline?
What defines a balanced pipeline?
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In the context of the laundry example, what is the average completion time for one task in a balanced pipeline?
In the context of the laundry example, what is the average completion time for one task in a balanced pipeline?
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What is a significant advantage of pipelining in CPU execution?
What is a significant advantage of pipelining in CPU execution?
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According to the properties of balanced pipelines, what happens to the time per instruction?
According to the properties of balanced pipelines, what happens to the time per instruction?
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What is the relationship between the number of pipe stages and the speedup of the pipelined execution?
What is the relationship between the number of pipe stages and the speedup of the pipelined execution?
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How does the example of pipelining in laundry illustrate the concept of executing multiple instructions?
How does the example of pipelining in laundry illustrate the concept of executing multiple instructions?
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What impact does pipelining have on task execution times compared to non-pipelined execution?
What impact does pipelining have on task execution times compared to non-pipelined execution?
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Which example illustrates the concept of 'pipelining' in a non-computational context?
Which example illustrates the concept of 'pipelining' in a non-computational context?
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What would be an effect of having unequal lengths of pipeline stages?
What would be an effect of having unequal lengths of pipeline stages?
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What is a primary advantage of Multiple Instruction Single Data (MISD) systems?
What is a primary advantage of Multiple Instruction Single Data (MISD) systems?
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Which of the following is a notable disadvantage of Multiple Instruction Multiple Data (MIMD) systems?
Which of the following is a notable disadvantage of Multiple Instruction Multiple Data (MIMD) systems?
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In the sequential laundry example, what is the total time taken for four students washing, drying, and folding clothes sequentially?
In the sequential laundry example, what is the total time taken for four students washing, drying, and folding clothes sequentially?
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What is a common use of MIMD organization in computing?
What is a common use of MIMD organization in computing?
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What does pipelining improve in the laundry task example?
What does pipelining improve in the laundry task example?
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Why are MISD systems not commonly available commercially?
Why are MISD systems not commonly available commercially?
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Which of the following statements about pipelining is accurate?
Which of the following statements about pipelining is accurate?
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When using MIMD organization, how do the processors operate?
When using MIMD organization, how do the processors operate?
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What is a primary challenge of implementing MIMD systems?
What is a primary challenge of implementing MIMD systems?
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Study Notes
Parallel Processing
- Parallel processing is the execution of concurrent events in computing to achieve faster computational speed.
- The goal is to speed up processing and increase throughput (amount of processing in a given time).
- Hardware increases with parallel processing, resulting in higher system costs.
- Technological advancements have reduced hardware costs, making parallel processing more feasible.
Parallel Processing Levels of Complexity
- Lower level: Serial shift registers versus parallel load registers.
- Higher level: Multiple functional units performing identical or different operations simultaneously.
Parallel Processing Classification
- Classification can be based on processor organization, interconnection structure, or information flow.
- One classification, by Flynn, categorizes systems based on instruction and data streams.
Parallel Processing Streams
- The normal computer operation fetches instructions from memory and executes in the processor.
- Instructions flow as an instruction stream.
- Data operations form a data stream.
- Parallel processing can occur in either or both streams.
Flynn's Classification
- SISD (Single Instruction Stream, Single Data Stream): A single processor with a single instruction stream operating on a single data stream. Includes sequential execution and may have internal parallel capabilities achieved through multiple functional units or pipelining.
- SIMD (Single Instruction Stream, Multiple Data Stream): Multiple processors execute the same instruction concurrently on different data items. Common in modern GPUs, vector processors, and array processors, often used extensively in image and digital signal processing.
- MISD (Multiple Instruction Stream, Single Data Stream): Multiple processors work on a single data stream, employing different instruction streams concurrently. This structure is theoretical with limited practical applications.
- MIMD (Multiple Instruction Stream, Multiple Data Stream): Multiple processors execute different instruction streams concurrently on different data items. This is the prevalent structure in most multiprocessor and multicomputer systems.
Single Instruction Stream, Single Data Stream (SISD)
- A single processor handles data from a single memory address.
- A single instruction is performed on data.
- Pipelining can be used for parallelism, but only one instruction is executed at a time.
- Single-processor systems are SISD.
- Advantages: Relatively inexpensive, low power consumption.
- Disadvantages: Limited processing speed due to single core.
- Uses: Microcontrollers and older mainframes.
Single Instruction Stream, Multiple Data Stream (SIMD)
- Multiple processing units execute the same instruction on distinct data.
- All processors receive the same instruction from a common control unit.
- Instructions can be executed sequentially or in parallel, leveraging pipelining.
- Advantages: Highly efficient for identical operations on large datasets.
- Disadvantages: Limited to specific applications.
- Uses: GPUs, scientific processing.
Multiple Instruction Stream, Single Data Stream (MISD)
- Multiple processors operate on a single data stream, each with its own set of instructions.
- A theoretical construct, no practical implementations.
Multiple Instruction Stream, Multiple Data Stream (MIMD)
- Multiple processors perform operations on several data elements independently or as a part of a shared memory space.
- Multiple instruction streams are executed simultaneously on different data streams.
- A primary organization for multi-processor and multi-computer systems.
- Advantages: Suitable for multitasking.
- Disadvantages: Complex architecture, often costly.
- Uses: Modern PCs, laptops, and smartphones.
Pipelining
- A technique for overlapping instructions in execution.
- An instruction can start processing before the prior instruction is fully complete.
- It speeds up operation in an otherwise non-parallel execution.
Laundry Example
- A practical, relatable example for understanding pipelining in action.
- Sequential washing leads to a much longer overall time than if the wash, dry, and fold tasks are overlapped (pipelined).
Balanced Pipeline
- Ideal pipeline where all stages have equal duration.
- With equal stage durations, tasks are completed far more quickly than the sum of each segment's duration.
- The slowest stage dictates the overall completion time of the task.
Pipelining Terminology
- Latency: The time taken for an instruction to complete.
- Throughput: The number of instructions completed per second.
- Clock cycle: Each computation step (like a clock tick).
- Processor cycle: Time for an instruction to progress one step in a pipeline.
- CPI (Clock Cycles Per Instruction): A measure of the processor's efficiency in executing instructions.
General Considerations for Pipelines
- Operations divisible into similar sub-operations lend themselves to pipelining.
- Pipeline segments (stages) are usually separated by registers that hold intermediate results.
- Clock cycles synchronized to ensure sequential, but overlapped, execution.
- Pipeline structure has potential to provide substantial speedup relative to a non-pipelined approach. But there are factors that can affect the speed achieved in a pipeline architecture.
Considerations for Pipelined Implementation
- Actual execution time is rarely equal to theoretical maximum speed up factors.
- Differences in time to compute a suboperation amongst stages will cause a lower performance than the theoretically maximum theoretical speedup.
- Non-ideal circuit designs may also affect speedup.
- Specific areas of computer design which leverage pipeline organization including arithmetic pipelines and instruction pipelines.
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Description
Test your knowledge on parallel processing architectures including SISD, SIMD, and MISD systems. This quiz will cover fundamental concepts such as pipelining and its applications in computing. Dive into the advantages and applications of these architectures with a set of diverse questions.
