Topic
Interpreted language
About: Interpreted language is a research topic. Over the lifetime, 512 publications have been published within this topic receiving 18315 citations. The topic is also known as: interpreted programming language.
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TL;DR: A new free suite of software tools designed to make this task easier, using the latest advances in hardware and software, written in the Python interpreted language using entirely free libraries are described.
3,575 citations
TL;DR: The wide spectrum of scientific applications of SAGA is highlighted in a review of published studies, with special emphasis on the core application areas digital terrain analysis, geomorphology, soil science, climatology and meteorology, as well as remote sensing.
Abstract: . The System for Automated Geoscientific Analyses (SAGA) is an open source geographic information system (GIS), mainly licensed under the GNU General Public License. Since its first release in 2004, SAGA has rapidly developed from a specialized tool for digital terrain analysis to a comprehensive and globally established GIS platform for scientific analysis and modeling. SAGA is coded in C++ in an object oriented design and runs under several operating systems including Windows and Linux. Key functional features of the modular software architecture comprise an application programming interface for the development and implementation of new geoscientific methods, a user friendly graphical user interface with many visualization options, a command line interpreter, and interfaces to interpreted languages like R and Python. The current version 2.1.4 offers more than 600 tools, which are implemented in dynamically loadable libraries or shared objects and represent the broad scopes of SAGA in numerous fields of geoscientific endeavor and beyond. In this paper, we inform about the system's architecture, functionality, and its current state of development and implementation. Furthermore, we highlight the wide spectrum of scientific applications of SAGA in a review of published studies, with special emphasis on the core application areas digital terrain analysis, geomorphology, soil science, climatology and meteorology, as well as remote sensing.
1,459 citations
01 Nov 2010
TL;DR: Soot, a framework for optimizing Java* bytecode, is implemented in Java and supports three intermediate representations for representing Java bytecode: Baf, a streamlined representation of bytecode which is simple to manipulate; Jimple, a typed 3-address intermediate representation suitable for optimization; and Grimp, an aggregated version of Jimple suitable for decompilation.
Abstract: This paper presents Soot, a framework for optimizing Java* bytecode. The framework is implemented in Java and supports three intermediate representations for representing Java bytecode: Baf, a streamlined representation of bytecode which is simple to manipulate; Jimple, a typed 3-address intermediate representation suitable for optimization; and Grimp, an aggregated version of Jimple suitable for decompilation. We describe the motivation for each representation, and the salient points in translating from one representation to another. In order to demonstrate the usefulness of the framework, we have implemented intraprocedural and whole program optimizations. To show that whole program bytecode optimization can give performance improvements, we provide experimental results for 12 large benchmarks, including 8 SPECjvm98 benchmarks running on JDK 1.2 for GNU/Linuxtm. These results show up to 8% improvement when the optimized bytecode is run using the interpreter and up to 21% when run using the JIT compiler.
1,160 citations
Book•
01 Dec 2000
TL;DR: This reference manual describes the syntax and ``core semantics'' of the Python language, which is terse, but attempts to be exact and complete.
Abstract: Python is a simple, yet powerful, interpreted programming language that bridges the gap between C and shell programming, and is thus ideally suited for ``throw-away programming'''' and rapid prototyping. Its syntax is put together from constructs borrowed from a variety of other languages; most prominent are influences from ABC, C, Modula-3 and Icon. The Python interpreter is easily extended with new functions and data types implemented in C. Python is also suitable as an extension language for highly customizable C applications such as editors or window managers. Python is available for various operating systems, amongst which several flavors of UNIX (including Linux), the Apple Macintosh O.S., MS-DOS, MS-Windows 3.1, Windows NT, and OS/2. This reference manual describes the syntax and ``core semantics'''' of the language. It is terse, but attempts to be exact and complete. The semantics of non-essential built-in object types and of the built-in functions and modules are described in the Python Library Reference. For an informal introduction to the language, see the Python Tutorial.
1,132 citations
15 Nov 2015
TL;DR: This paper presents a just-in-time compiler for Python that focuses in scientific and array-oriented computing, Numba, which compiles a subset of the language into efficient machine code that is comparable in performance to a traditional compiled language.
Abstract: Dynamic, interpreted languages, like Python, are attractive for domain-experts and scientists experimenting with new ideas. However, the performance of the interpreter is often a barrier when scaling to larger data sets. This paper presents a just-in-time compiler for Python that focuses in scientific and array-oriented computing. Starting with the simple syntax of Python, Numba compiles a subset of the language into efficient machine code that is comparable in performance to a traditional compiled language. In addition, we share our experience in building a JIT compiler using LLVM[1].
1,032 citations