Garbage Collection in Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1922 105.28 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1924 105.29 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 167 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

Garbage Collection in Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1922 105.28 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1924 105.29 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 167 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

Garbage Collection in Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1922 105.28 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1924 105.29 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 167 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

Julia + MMTk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1976 106.29 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1978 106.30 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 168 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

Garbage Collection in Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1972 106.28 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1974 106.29 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 168 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

Garbage Collection in Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1972 106.28 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1974 106.29 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 168 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

Garbage Collection in Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1972 106.28 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1974 106.29 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 168 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

Garbage Collection in Julia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1963 105.28 JIT Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1965 105.29 Core typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm ability to statically infer and compile code to run fast, without theCHAPTER 13. METHODS 168 usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment

typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm This is key to Julia's ability to statically infer and compile code to run fast, without the usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment SharedArray{Float64,3}((500,500,500)); julia> u = SharedArray{Float64,3}((500,500,500)); Run the functions once to JIT-compile and @time them on the second run: julia> @time advection_serial!(q, u); (irange,jrange,trange)

typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation (and optional ahead-of-time compilation), implemented using LLVM. It is multi-paradigm This is key to Julia's ability to statically infer and compile code to run fast, without the usual JIT tricks and overhead. Indeed, any new method definition won't be visible to the current runtime environment SharedArray{Float64,3}((500,500,500)); julia> u = SharedArray{Float64,3}((500,500,500)); Run the functions once to JIT-compile and @time them on the second run: julia> @time advection_serial!(q, u); (irange,jrange,trange)