On the Performance of the Python Programming Language for Serial and Parallel Scientific Computations

Cai, Xing; Langtangen, Hans Petter; Moe, Halvard

doi:10.1155/2005/619804

Cited by 62 publications

(33 citation statements)

References 14 publications

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“…Further, the general scientific computational performance of Python is well document by many papers and projects; see e.g. the comprehensive paper by Cai et al (2005) [13].…”

Section: B Motivation and Goalsmentioning

confidence: 99%

Real-time analysis of a multi-robot sewing cell

Schrimpf

Lind

Mathisen

2013

2013 IEEE International Conference on Industrial Technology (ICIT)

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SummaryThis PhD thesis presents topics related to sensor-based real-time robot control in applied automation.While in the past industrial challenges often could be solved with traditional robot programming methods, the industry looks more and more towards the automation of complex tasks that need real-time sensor-feedback in the control loop of the robot. This is especially important in applications where the workpiece shape or characteristics are uncertain or unknown. When working on such workpieces, the movement has to be adjusted in real-time, ie. while the robot is moving. To achieve this, sensors are added in the control loop of the robot.One challenge for the implementation of industrial solutions including real-time control is the lack of appropriate interfaces in most commercially available robots. When such interfaces are not present, in-house developed solutions can be used to access the low-level system of the robots, at least for research applications. These usually require modifications of the hardware, the software platform or both. Often, interfaces are implemented that allows for parts of the control loop being moved to an external PC. In this thesis, real-time interfaces for two different industrial manipulators are presented that are used for lab experiments and demonstrators. The real-time interfaces work position-based and have update frequencies of about 100 Hz. Ethernet UDP is used to communicate with the external controller platform. Experiments are presented that measure the delays in the low-level systems of the robots.To externally control the movement of the real-time controlled robots from an application controller, a trajectory generator is needed. This thesis gives an overview of three different on-line trajectory generators that were in-house developed. The real-time capabilities of the presented trajectory generators were analyzed in order to ensure that the requirement for response times of the real-time interfaces are met.Based on a presented real-time interface and trajectory generator, a iii iv test platform was built. The test platform demonstrates tracking of a line that is sketched on the workpiece. The robot tool is controlled to keep a fixed distance between tool and workpiece, while maintaining an orientation perpendicular to the workpiece surface. The line tracking is done using a line-of-sight based control method. Experiments are presented, measuring the delays in the robot-sensor system. The main part of this thesis is a presentation of an automated robotic sewing cell that demonstrates a case of sewing for the furniture industry. The system is able to sew together two parts with slightly different shapes. A two-robot solution is presented that controls the work pieces independently during the sewing operation. A force sensor is integrated in the control system to keep a constant sewing force. The seam allowance is controlled by an edge control system based on optical sensors that are mounted on the sewing machine. The real-time capabilities of the system are analyze...

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“…Further, the general scientific computational performance of Python is well document by many papers and projects; see e.g. the comprehensive paper by Cai et al (2005) [13].…”

Section: B Motivation and Goalsmentioning

confidence: 99%

Real-time analysis of a multi-robot sewing cell

Schrimpf

Lind

Mathisen

2013

2013 IEEE International Conference on Industrial Technology (ICIT)

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“…Python is a high-level interpreted language. For many cases it will be slower in execution time than its C/C++ equivalents [8]. As mentioned before, the Python language is flexible in the manner of glueing with other languages.…”

Section: Performance Considerationmentioning

confidence: 99%

Developing of Scientific Software Applications in Python. I. Transformation of Hubbard Hamiltonian into the Matrix and its Diagonalization

Herok

Szczȩśniak

Durajski

2015

CMST

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In order to perform larger scale physics research in the area of superconductivity, we have developed an application that can transform the Hubbard Hamiltonian into a matrix and diagonalize it to find the selected model's energy spectrum. For that purpose we have used the Python language and its wide ecosystem. This paper proves that selected tools are capable of creating scientific applications in a general sense. After a short introduction into the physics problem and the designed algorithm we will present the computer science problems and their solutions in creating usual scientific programs, in particular: performance and parallelization issues, storage of input data and the results, bottlenecks detections, as well as optimization and testing. The most interesting examples of the developing cycle will be described to give a prepared solution for implementing the other scientific software.

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“…For certain tasks, particularly very lowlevel tasks, or those on low-performance computers such as some embedded systems, statically typed languages retain an important advantage. However it is interesting to note that in certain dataintensive and performance sensitive domains, such as scientific computing, untyped languages have proved to be very successful [6]. Also dynamism is very important for data intensive programming, where queries are often generated dynamically based on runtime information, and thus the structure of the query results is not known statically.…”

Section: Addressing Negatives Of Dynamic Typingmentioning

confidence: 99%