CS401 GDB Solution Spring 2022
Question
Performance evaluation is at the foundation of computer architecture
research and development. Present-day microprocessors are so complex that
architects cannot design systems based on intuition and simple models only.
Adequate performance evaluation methods are crucial to leading the research and
development process in the right direction. To embed the parallelism in the
processor as well as accuracy, modularity, power, and predictability as the key
performance measures, what do you think how the systems should be developed
while taking the consideration of hardware infrastructure prototypes or
simulation-based design?
You are hereby required to select one of the given above design approaches
along with three specific reasons to select your model. Give a precise and
to-the-point answer not more than five lines.
Demo Solution:
Performance
evaluation is at the foundation of computer architecture research and
development. Contemporary microprocessors are so complex that architects cannot
design systems based on intuition and simple model only. Adequate performance
evaluation methods are absolutely crucial to steer the research and development
process in the right direction. However, rigorous performance evaluation is
non-trivial as there are multiple aspects to performance evaluation, such as
picking workloads, selecting an appropriate modeling or simulation approach,
running the model and interpreting the results using meaningful metrics. Each of
these aspects is equally important and a performance evaluation method that
lacks rigor in any of these crucial aspects may lead to inaccurate performance
data and may drive research and development in a wrong direction. The goal of
this book is to present an overview of the current state-of-the-art in computer
architecture performance evaluation, with a special emphasis on methods for
exploring processor architecture.
The book focuses on
fundamental concepts and ideas for obtaining accurate performance data. The
book covers various topics in performance evaluation, ranging from performance
metrics, to workload selection, to various modeling approaches including
mechanistic and empirical modeling. And because simulation is by far the most
prevalent modeling technique, more than half the book's content is devoted to
simulation. The book provides an overview of the simulation techniques in the
compute designer's toolbox, followed by various simulation acceleration
techniques including sampled simulation, statistical simulation, parallel
simulation and hardware- accelerated simulation
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