Tutorial on Profiling Software Execution #775
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wwarriner
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Aug 23, 2024
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| # Profiling | |||
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| Profiling is essential for assessing how different parts of a program execute and gathering crucial performance data. It plays a vital role in debugging, pinpointing bottlenecks, optimizing code, and scaling application performance. This analysis identifies common issues such as out-of-bound memory, segmentation faults, bus errors, and runtime overhead, enabling effective troubleshooting and improvement strategies. | |||
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Please define some of these terms.
- out-of-bounds memory
- segmentation fault
- bus error
- runtime
- bottleneck
| 2. Memory Profling | ||
| 3. CPU Profling | ||
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| !!! note |
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Make sure to fix this admonition, it doesn't appear to be formatted correctly.
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| ## Profiling Python Codes | ||
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| Three common profiling techniques used in analyzing Python codes are discussed briefly in this section. |
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In a short paragraph, give the purpose for each. Why would I want to use time vs CPU vs memory profiling?
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| The following example shows profiling a input python code that calculates num_array. | ||
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| ```bash |
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Pull Request
A tutorial on Profiling software execution.
Overview
This tutorial page introduces various profiling techniques for analyzing software execution, with a focus on analyzing Python-based code.
Proposed Changes
Related Issues
Partial fix of #504