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Computer Architecture: Performance

The Classic CPU Performance Equation in terms of instruction count (the number of instructions executed by the program), CPI, and clock cycle time: CPU time=Instruction count * CPI * Clock cycle time

PERFORMANCE

CPU performance equation.

The Classic CPU Performance Equation in terms of instruction count (the number of instructions executed by the program), CPI, and clock cycle time: CPU time=Instruction count * CPI * Clock cycle time or since the clock rate is the inverse of clock cycle time:

CPU time = Instruction count *CPI / Clock rate

T = N X S  / R

Relative performance:

Performance A / Performance B = Execution time B / Execution time A = n

CPU execution time for a program

CPU execution time for a program = CPU clock cycles for a program * clock cycle time or since the clock rate is the inverse of clock cycle time:

CPU execution time for a program=  CPU clock cycles for a program / Clock rate


CPU clock cycles required for a program

CPU clock cycles = Instructions for a program * Average clock cycles per instruction


Basic components of performance

The basic components of performance and how each is measured are:


Components of Performance

CPU execution time for a program

Instruction count

Clock cycles per instruction(CPI)

Clock cycle time

 

Units of measure

Seconds for the program

Instruction executed for the program

Average number of clock cycles per instruction

Seconds per clock cycle

CPU execution time for a program = CPU clock cycles for a program * Clock cycle time.

 

Factors affecting the CPU performance

The performance of a program depends on the algorithm, the language, the compiler, the architecture, and the actual hardware. The following list summarizes how these components affect the factors in the CPU performance equation.

1. Algorithm –affects Instruction count, possibly CPI

The algorithm determines the number of source program instructions executed and hence the number of processor instructions executed. The algorithm may also affect the CPI, by favoring slower or faster instructions. For example, if the algorithm uses more floating-point operations, it will tend to have a higher CPI.

2. Programming language - affects Instruction count,CPI

The programming language certainly affects the instruction count, since statements in the language are translated to processor instructions, which determine instruction count. The language may also affect the CPI because of its features; for example, a language with heavy support for data abstraction (e.g., Java) will require indirect calls, which will use higher-CPI instructions.

 

3. Compiler - affects Instruction count, CPI

The efficiency of the compiler affects both the instruction count and average cycles per instruction, since the compiler determines the translation of the source language instructions into computer instructions. The compiler’s role can be very complex and affect the CPI in complex ways.

 

4. Instruction set architecture - affects Instruction count, clock rate, CPI

The instruction set architecture affects all three aspects of CPU performance, since it affects the instructions needed for a function, the cost in cycles of each instruction, and the overall clock rate of the processor.

 

Amdahl’s law

Amdahl's law states that the performance improvement to be gained from using some faster mode of execution is limited by the fraction of the time the faster mode can be used.

Speedup=  Performance for entire task using the enhancement / Performance for entire task without using the enhancement

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FAQs on Performance - Computer Architecture and Performance, Computer Science and IT Engineering - Computer Science Engineering (CSE)

1. What is computer architecture and how does it relate to performance?
Answer: Computer architecture refers to the design and organization of computer systems, including the components and their interconnections. It plays a crucial role in determining the performance of a computer system. The architecture affects factors such as processing speed, memory capacity, and input/output capabilities, which directly impact the overall performance of the system.
2. What are the main factors that influence computer performance?
Answer: Several factors influence computer performance, including the processor speed, memory capacity, disk storage speed, and the efficiency of the operating system and software being used. Additionally, the architecture of the computer system, such as the arrangement of components and the design of the memory hierarchy, also significantly impacts performance.
3. How can computer architecture be optimized to improve performance?
Answer: Computer architecture can be optimized to enhance performance by employing techniques such as pipelining, caching, and parallel processing. Pipelining allows for the simultaneous execution of multiple instructions, caching stores frequently accessed data closer to the processor for faster retrieval, and parallel processing involves dividing tasks among multiple processors to execute them simultaneously, thus increasing overall performance.
4. What is the role of computer science and IT engineering in computer architecture and performance?
Answer: Computer science and IT engineering play a crucial role in the development and improvement of computer architecture and performance. They contribute to the design and analysis of computer systems, develop algorithms and software for optimizing performance, and explore new technologies and techniques to enhance the efficiency and effectiveness of computer systems.
5. What are some common challenges in computer architecture and performance optimization?
Answer: Some common challenges in computer architecture and performance optimization include balancing trade-offs between performance and power consumption, addressing bottlenecks in memory access and data transfer, handling complex instruction sets, and ensuring compatibility across different architectures and software. Additionally, with the increasing demand for high-performance computing, scalability and parallelism are also significant challenges in optimizing computer architecture and performance.
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