Julia 1.12.0 RC1numeric values that cannot be represented effectively in native hardware representations, but at the cost of relatively slower performance. The following are Julia's primitive numeric types: • Integer types: functions Generated functions can achieve high efficiency at run time, but come with a compile time cost: a new function body must be generated for every combination of concrete argument types. Typically strongly recommended for interoperable code. In this case, there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permitted to pass strings). Note0 码力 | 2057 页 | 7.44 MB | 3 月前3
Julia 1.12.0 Beta4numeric values that cannot be represented effectively in native hardware representations, but at the cost of relatively slower performance. The following are Julia's primitive numeric types: • Integer types: functions Generated functions can achieve high efficiency at run time, but come with a compile time cost: a new function body must be generated for every combination of concrete argument types. Typically strongly recommended for interoperable code. In this case, there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permitted to pass strings). Note0 码力 | 2057 页 | 7.44 MB | 3 月前3
Julia 1.12.0 Beta3numeric values that cannot be represented effectively in native hardware representations, but at the cost of relatively slower performance. The following are Julia's primitive numeric types: • Integer types: functions Generated functions can achieve high efficiency at run time, but come with a compile time cost: a new function body must be generated for every combination of concrete argument types. Typically strongly recommended for interoperable code. In this case, there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permitted to pass strings). Note0 码力 | 2057 页 | 7.44 MB | 3 月前3
julia 1.12.0 beta1numeric values that cannot be represented effectively in native hardware representations, but at the cost of relatively slower performance. The following are Julia's primitive numeric types: • Integer types: functions Generated functions can achieve high efficiency at run time, but come with a compile time cost: a new function body must be generated for every combination of concrete argument types. Typically strongly recommended for interoperable code. In this case, there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permitted to pass strings). Note0 码力 | 2047 页 | 7.41 MB | 3 月前3
Julia v1.2.0 Documentationnumeric values that cannot be represented effec�vely in na�ve hardware representa�ons, but at the cost of rela�vely slower performance. The following are Julia's primi�ve numeric types: • Integer types: Op�onally-generated func�ons Generated func�ons can achieve high efficiency at run �me, but come with a compile �me cost: a new func�on body must be generated for every combina�on of concrete argument types. Typically, strongly recommended for interoperable code. In this case there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permi�ed to pass strings). Note A0 码力 | 1250 页 | 4.29 MB | 1 年前3
Julia v1.1.1 Documentationnumeric values that cannot be represented effec�vely in na�ve hardware representa�ons, but at the cost of rela�vely slower performance. The following are Julia's primi�ve numeric types: • Integer types: Op�onally-generated func�ons Generated func�ons can achieve high efficiency at run �me, but come with a compile �me cost: a new func�on body must be generated for every combina�on of concrete argument types. Typically, strongly recommended for interoperable code. In this case there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permi�ed to pass strings). Note A0 码力 | 1216 页 | 4.21 MB | 1 年前3
Julia 1.1.0 Documentationnumeric values that cannot be represented effec�vely in na�ve hardware representa�ons, but at the cost of rela�vely slower performance. The following are Julia's primi�ve numeric types: • Integer types: Op�onally-generated func�ons Generated func�ons can achieve high efficiency at run �me, but come with a compile �me cost: a new func�on body must be generated for every combina�on of concrete argument types. Typically, strongly recommended for interoperable code. In this case there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permi�ed to pass strings). Note A0 码力 | 1214 页 | 4.21 MB | 1 年前3
Julia 1.2.0 DEV Documentationnumeric values that cannot be represented effec�vely in na�ve hardware representa�ons, but at the cost of rela�vely slower performance. The following are Julia's primi�ve numeric types: • Integer types: Op�onally-generated func�ons Generated func�ons can achieve high efficiency at run �me, but come with a compile �me cost: a new func�on body must be generated for every combina�on of concrete argument types. Typically, strongly recommended for interoperable code. In this case there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permi�ed to pass strings). Note A0 码力 | 1252 页 | 4.28 MB | 1 年前3
julia 1.13.0 DEVnumeric values that cannot be represented effectively in native hardware representations, but at the cost of relatively slower performance. The following are Julia's primitive numeric types: • Integer types: functions Generated functions can achieve high efficiency at run time, but come with a compile time cost: a new function body must be generated for every combination of concrete argument types. Typically strongly recommended for interoperable code. In this case, there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permitted to pass strings). Note0 码力 | 2058 页 | 7.45 MB | 3 月前3
Julia v1.4.2 Documentationnumeric values that cannot be represented effectively in native hardware representations, but at the cost of relatively slower performance. The following are Julia's primitive numeric types: • Integer types: functions Generated functions can achieve high efficiency at run time, but come with a compile time cost: a new function body must be generated for every combination of concrete argument types. Typically strongly recommended for interoperable code. In this case there will be no hidden arguments, at the cost of some language features (e.g. only character(len=1) will be permitted to pass strings). Note0 码力 | 1314 页 | 4.29 MB | 1 年前3
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