As computers become more complex, the number and complexity of the tasks facing the computer architect have increased. Computer performance often depends in complex way on the design parameters and intuition that must be supplemented by performance studies to enhance design productivity.
This book introduces computer architects to computer system performance models and shows how they are relatively simple, inexpensive to implement, and sufficiently accurate for most purposes. It discusses the development of performance models based on queuing theory and probability. The text also shows how they are used to provide quick approximate calculations to indicate basic performance tradeoffs and narrow the range of parameters to consider when determining system configurations. It illustrates how performance models can demonstrate how a memory system is to be configured, what the cache structure should be, and what incremental changes in cache size can have on the miss rate. A particularly deep knowledge of probability theory or any other mathematical field to understand the papers in this volume is not required.Preface.
Computer Performance Evaluation Methodology.
An Instruction Timing Model of CPU Performance.
On Parallel Processing Systems: Amdahl's Law Generalized and Some Results on Optimal Design.
The Nonuniform Distribution of Instruction-Level and Machine Parallelism and Its Effect on Performance.
Classification and Performance Evaluation of Instruction Buffering Techniques.
Characterization of Branch and Data Dependencies in Programs for Evaluating Pipeline Performance.
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