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1. #RUN PYTHON EMULATOR MAC MAC OS#
2. #RUN PYTHON EMULATOR MAC INSTALL#
3. #RUN PYTHON EMULATOR MAC SERIAL#
4. #RUN PYTHON EMULATOR MAC ARCHIVE#

#RUN PYTHON EMULATOR MAC INSTALL#

Run the setup script: python setup.py install

#RUN PYTHON EMULATOR MAC ARCHIVE#

InstallationĪny platform: download a module archive and extract it to a local directory. Cross-platform portability and dynamic load-balancing allows Parallel Python to parallelize computations efficiently even on heterogeneous and multi-platform clusters. To make things even better, the software written with Parallel Python works in parallel even on many computers connected via local network or Internet. All the details and complexity of the latter are completely taken care of, and your application just submits jobs and retrieves their results (the easiest way to write parallel applications). Internally ppsmp uses processes and IPC (Inter Process Communications) to organize parallel computations. Parallel Python module overcomes this limitation and provides a simple way to write parallel python applications. This lock allows to execute only one python byte-code instruction at a time even on an SMP computer. The reason is that python interpreter uses GIL (Global Interpreter Lock) for internal bookkeeping. Although, it appears that if the application is computation-bound using 'thread' or 'threading' python modules will not allow to run python byte-code in parallel. The most simple and common way to write parallel applications for SMP computers is to use threads. This together with wide availability of SMP computers (multi-processor or multi-core) and clusters (computers connected via network) on the market create the demand in parallel execution of python code.

Nowadays software written in python finds applications in broad range of the categories including business logic, data analysis and scientific calculations. Cross-architecture portability and interoperability (x86, x86-64, etc.).

#RUN PYTHON EMULATOR MAC MAC OS#

Low overhead for subsequent jobs with the same function (transparent caching is implemented to decrease the overhead).Dynamic processors allocation (number of worker processes can be changed at runtime).Automatic detection of the optimal configuration (by default the number of worker processes is set to the number of effective processors).

#RUN PYTHON EMULATOR MAC SERIAL#

Easy to understand and implement job-based parallelization technique (easy to convert serial application in parallel).Parallel execution of python code on SMP and clusters.Parallel Python is an open source and cross-platform module written in pure python It is light, easy to install and integrate with other python software. Parallel Python is a python module which provides mechanism for parallel execution of python code on SMP (systems with multiple processors or cores) and clusters (computers connected via network).