. . . . . . . . . . . . . . . . . . 122 12.10类型别名 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 12.11类型操作 . . . . . . . . . . . . . . . . . . . . . . . . 140 13.7 可选参数和关键字的参数的注意事项 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 13.8 类函数对象 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 13 JULIA_NUM_THREADS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277 JULIA_THREAD_SLEEP_THRESHOLD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 JULIA_EXCLUSIVE

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multiple threads By default, Julia starts up with 2 threads of execution; 1 worker thread and 1 interactive thread. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads(:default)

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multiple threads By default, Julia starts up with 2 threads of execution; 1 worker thread and 1 interactive thread. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads(:default)

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multiple threads By default, Julia starts up with 2 threads of execution; 1 worker thread and 1 interactive thread. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads(:default)

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multiple threads By default, Julia starts up with 2 threads of execution; 1 worker thread and 1 interactive thread. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads(:default)

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multiple threads By default, Julia starts up with 2 threads of execution; 1 worker thread and 1 interactive thread. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads(:default)

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multi-threading features. 25.1 Starting Julia with multiple threads By default, Julia starts up with a single thread of execution. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads()

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 362 27.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 27.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multi-threading features. 24.1 Starting Julia with multiple threads By default, Julia starts up with a single thread of execution. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads()

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multi-threading features. 25.1 Starting Julia with multiple threads By default, Julia starts up with a single thread of execution. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads()

Accessing Data through a Pointer . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 28.16 Thread-safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 28.17 More Multi-threading: Julia's multi-threading provides the ability to schedule Tasks simultaneously on more than one thread or CPU core, sharing memory. This is usually the easiest way to get parallelism on one's PC or on multi-threading features. 25.1 Starting Julia with multiple threads By default, Julia starts up with a single thread of execution. This can be verified by using the command Threads.nthreads(): julia> Threads.nthreads()