and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). Chapter 40 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 43 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 43.1 Avoid global variables A global

applica�ons, and we do not expect their use to diminish. Fortunately, modern language design and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a single environment microseconds on the author's laptop). Chapter 42 Memory alloca�on analysis One of the most common techniques to improve performance is to reduce memory alloca�on. The total amount of alloca�on can be measured jl_apply_generic! Chapter 45 Performance Tips In the following sec�ons, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 45.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). Chapter 33 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 36 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 36.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). 32.5 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 34 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 34.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). 32.5 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 34 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 34.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). 32.5 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 34 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 34.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). Chapter 33 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 36 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 36.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). Chapter 40 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 43 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 43.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). Chapter 40 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 43 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 43.1 Avoid global variables A global

and we do not expect their use to diminish. Fortunately, modern language de- sign and compiler techniques make it possible to mostly eliminate the performance trade-off and provide a sin- gle environment microseconds on the author's laptop). 32.5 Memory allocation analysis One of the most common techniques to improve performance is to reduce memory allocation. The total amount of allocation can be measured jl_apply_generic! Chapter 34 Performance Tips In the following sections, we briefly go through a few techniques that can help make your Julia code run as fast as possible. 34.1 Avoid global variables A global