Genetic Algorithms on GPU using Intel Distribution of Python numba-dpex code sample

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Add Genetic Algorithms on GPU using Intel Distribution of Python numba-dpex code sample

Description

This sample shows how to implement general generic algorithm (GA) and offload computation to GPU using numba-dpex. It also demonstrates how to adjust GA methods to specific optimization problem which is Traveling Salesman Problem.

Checklist

Administrative

• [ ] Review sample design with the appropriate Domain Expert:
• [ ] If you have any new dependencies/binaries, inform the oneAPI Code Samples Project Manager

Code Development

• [X] Implement coding guidelines and ensure code quality. see wiki for details
• [X] Adhere to readme template
• [X] Adhere to sample.json specification. https://github.com/oneapi-src/oneAPI-samples/wiki/sample-json-specification
• [X] Ensure/create CI test configurations for sample (ciTests field) https://github.com/oneapi-src/oneAPI-samples/wiki/sample-json-ci-test-object
• [X] Run jsonlint on sample.json to verify json syntax. www.jsonlint.com

Security and Legal

• [ ] OSPDT Approval (see Project Manager for assistance)
• [ ] Compile using the following compiler flags and fix any warnings, the falgs are: "/Wall -Wformat-security -Werror=format-security"
• [ ] Bandit Scans (Python only)
• [ ] Virus scan

Review

• [ ] Review DPC++ code with Paul Peterseon. (GitHub User: pmpeter1)
• [ ] Review readme with Tom Lenth(@tomlenth) and/or Project Manager
• [X] Tested using Dev Cloud when applicable