with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414 34 Performance Tips 416 34.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 416 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 34.3 Measure performance with @time and pay attention to memory allocation . . . . . . 417 34.4 Tools . . . . . . . . Tweaks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 34.23 Performance Annotations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 34.24 Treat Subnormal

with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414 34 Performance Tips 416 34.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 416 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 34.3 Measure performance with @time and pay attention to memory allocation . . . . . . 417 34.4 Tools . . . . . . . . Tweaks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 34.23 Performance Annotations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 34.24 Treat Subnormal

with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 35 Performance Tips 444 35.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 444 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 35.3 Measure performance with @time and pay attention to memory allocation . . . . . . 445 35.4 Tools . . . . . . . . Tweaks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467 35.25 Performance Annotations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 468 35.26 Treat Subnormal

with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 35 Performance Tips 444 35.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 444 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 35.3 Measure performance with @time and pay attention to memory allocation . . . . . . 445 35.4 Tools . . . . . . . . Tweaks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467 35.25 Performance Annotations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 468 35.26 Treat Subnormal

with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 35 Performance Tips 444 35.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 444 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 35.3 Measure performance with @time and pay attention to memory allocation . . . . . . 445 35.4 Tools . . . . . . . . Tweaks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467 35.25 Performance Annotations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 468 35.26 Treat Subnormal

Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 35 Performance Tips 454 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1182 51.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1185 51.5 Design inspiration . . . . . . . . blogs on Julia 1.2 Introduction Scientific computing has traditionally required the highest performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe

Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452 35 Performance Tips 455 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1180 51.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1183 51.5 Design inspiration . . . . . . . . blogs on Julia 1.2 Introduction Scientific computing has traditionally required the highest performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe

Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 35 Performance Tips 454 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1179 51.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1182 51.5 Design inspiration . . . . . . . . blogs on Julia 1.2 Introduction Scientific computing has traditionally required the highest performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe

Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 35 Performance Tips 454 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1179 51.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1182 51.5 Design inspiration . . . . . . . . blogs on Julia 1.2 Introduction Scientific computing has traditionally required the highest performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe

Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 35 Performance Tips 454 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1171 50.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1174 50.5 Design inspiration . . . . . . . . blogs on Julia 1.2 Introduction Scientific computing has traditionally required the highest performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe