Julia 1.11.4Julia Homepage • Download Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2007 页 | 6.73 MB | 3 月前3- Julia 1.11.5 DocumentationJulia Homepage • Download Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2007 页 | 6.73 MB | 3 月前3
- Julia 1.11.6 Release Notes• Julia Homepage • Install Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2007 页 | 6.73 MB | 3 月前3
- julia 1.10.10• Julia Homepage • Install Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 1692 页 | 6.34 MB | 3 月前3
- Julia 1.10.9Julia Homepage • Download Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 1692 页 | 6.34 MB | 3 月前3
- Julia 1.12.0 RC1• Julia Homepage • Install Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2057 页 | 7.44 MB | 3 月前3
- Julia 1.12.0 Beta4• Julia Homepage • Install Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2057 页 | 7.44 MB | 3 月前3
- Julia 1.12.0 Beta3• Julia Homepage • Install Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2057 页 | 7.44 MB | 3 月前3
- julia 1.12.0 beta1Julia Homepage • Download Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2047 页 | 7.41 MB | 3 月前3
- julia 1.13.0 DEV• Julia Homepage • Install Julia • Discussion forum • Julia YouTube • Find Julia Packages • Learning Resources • Read and write blogs on Julia 1.2 Introduction Scientific computing has traditionally the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled0 码力 | 2058 页 | 7.45 MB | 3 月前3
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