TI-BASIC:Better Code Timings - Revision history

lirtosiast: /* Variable Access */

2016-05-03T17:45:04Z

Variable Access

← Older revision		Revision as of 17:45, 3 May 2016
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	\| Constant 1 \|\| 1000 \|\| 0 (by def) \|\| 2.55MP jsTIfied / lirtosiast		\| Constant 1 \|\| 1000 \|\| 0 (by def) \|\| 2.55MP jsTIfied / lirtosiast
	\|-		\|-
	\| ~~All system vars~~ \|\| 1000 \|\| 0.11 \|\| "		\| Constant pi \|\| 1000 \|\| -.02 \|\| "
	\|-		\|-
	\| X (L1~L6 deleted) \|\| 1000 \|\| 0.47 ~~\|\| "~~		\| Constant i \|\| 1000 \|\| -.08 \|\| "
			\|-
			\| All system vars \|\| 1000 \|\| 0.11
			\|-
			\| X (L1~L6 deleted) \|\| 1000 \|\| 0.47
	\|-		\|-
	\| X (L1-L6 not deleted) \|\| 1000 \|\| 0.48		\| X (L1-L6 not deleted) \|\| 1000 \|\| 0.48

lirtosiast: /* Variable Access */

2016-05-03T17:42:21Z

Variable Access

← Older revision		Revision as of 17:42, 3 May 2016
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	==Variable Access==		==Variable Access==

	All variables are equal to 1. The following timings include storing to Ans as overhead.		All variables are equal to 1. The following timings include storing to Ans as overhead. Code was executed immediately after RAM clear.

	{\| class="wikitable"		{\| class="wikitable"
	! Variable \|\| Iters \|\| Time (ms) \|\| Username		! Variable \|\| Iters \|\| Time (ms) \|\| Username
	\|-		\|-
	\| ~~All system vars~~ \|\| 1000 \|\| 0~~.11~~ \|\| 2.55MP jsTIfied / lirtosiast		\| Constant 1 \|\| 1000 \|\| 0 (by def) \|\| 2.55MP jsTIfied / lirtosiast
	\|-		\|-
	\| X (L1~L6 deleted) \|\| 1000 \|\| \|\| ''		\| All system vars \|\| 1000 \|\| 0.11 \|\| "
			\|-
			\| X (L1~L6 deleted) \|\| 1000 \|\| 0.47 \|\| "
			\|-
			\| X (L1-L6 not deleted) \|\| 1000 \|\| 0.48
			\|-
			\| X (after 26 other real vars created) \|\| 1000 \|\| 0.79
			\|-
			\| Z (after 26 other real vars created) \|\| 1000 \|\| 0.79
			\|}

			The following timings do not include storing to Ans as overhead.

			{\| class="wikitable"
			! Variable \|\| Value \|\| Iters \|\| Time (ms) \|\| Username
			\|-
			\| Str1 \|\| "A" \|\| 1000 \|\| 1.95 \|\| "
			\|-
			\| Str1 \|\| 100 "A"s \|\| 1000 \|\| 2.09
	\|}		\|}

lirtosiast: /* Instructions */

2016-05-03T17:29:04Z

Instructions

← Older revision		Revision as of 17:29, 3 May 2016
Line 1:		Line 1:
	= Instructions =		= Instructions =

	First, write the name and model of your calculator in the table below, then use this code to measure your loop overhead (~~without~~ an empty line).		First, write the name and model of your calculator in the table below, then use this code to measure your loop overhead (with an empty line).

	Add the number of iterations you used to the "iterations" column, and [time taken~~]/[iterations]~~ to the "average" column. Then subtract your loop overhead from the result and list it in the "time" column.		Add the number of iterations you used to the "iterations" column, and the calculated time taken to the "average" column. Then subtract your loop overhead from the result and list it in the "time" column.

	FnOff		FnOff
Line 12:		Line 12:
	0→Ymax		0→Ymax
	DispGraph //if it is a graphing command		DispGraph //if it is a graphing command
	~~startTmr→θ~~		1000->I% //iterations
	~~Repeat checkTmr~~(θ		startTmr->Tmin
			While startTmr=Tmin:End
			For([recursiven],1,I%
			1
	End		End
	For(~~𝑛1,~~[~~iterations~~]~~) //sequence variable 𝑛; note the closing parenthesis.~~		startTmr->Tmax
	~~//test code here~~		For([recursiven],1,\|E9:
			If startTmr=Tmax
	End		End
	~~checkTmr~~(θ+1		Disp (Tmax-Tmin-1+round(1-[recursiven]/99,2)-0.63)/I%*1000

			Alternatively, use the following timing code to include storing to Ans (":1") in the overhead:

			1000->I%
			startTmr->Tmin
			While startTmr=Tmin:End
			For([recursiven],1,I%
			[code]
			End
			startTmr->Tmax
			For([recursiven],1,\|E9:
			If startTmr=Tmax
			End
			Disp (Tmax-Tmin-1+round(1-[recursiven]/99,2)-1.74)/I%*1000

			In either case, you must calibrate these loop overheads to your own calculator's speed.

	__TOC__		__TOC__

			==Variable Access==

			All variables are equal to 1. The following timings include storing to Ans as overhead.
			{\| class="wikitable"
			! Variable \|\| Iters \|\| Time (ms) \|\| Username
			\|-
			\| All system vars \|\| 1000 \|\| 0.11 \|\| 2.55MP jsTIfied / lirtosiast
			\|-
			\| X (L1~L6 deleted) \|\| 1000 \|\| \|\| ''
			\|}

	== Math Commands ==		== Math Commands ==
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	\|-		\|-
	\| For(''n'',1,100000 \|\| .69 \|\| kgmstwo		\| For(''n'',1,100000 \|\| .69 \|\| kgmstwo
			\|-
			\| incl. ":1" \|\| 1.74 \|\| 2.55MP jsTIfied / lirtosiast
	\|}		\|}

lirtosiast: /* Matrix Commands */

2016-03-30T02:15:47Z

Matrix Commands

← Older revision		Revision as of 02:15, 30 March 2016
Line 129:		Line 129:
	\|}		\|}

	~~Here it can be seen clearly~~ that matrix multiplication should not be used to re-order the rows or columns of a matrix when speed is a priority. Use rowSwap( instead: ten rowSwap( take 0.17 seconds while one multiplication takes 11.8 seconds.		It is clear that matrix multiplication should not be used to re-order the rows or columns of a matrix when speed is a priority. Use rowSwap( instead: ten rowSwap( take 0.17 seconds while one multiplication takes 11.8 seconds.

	{\| class="wikitable"		{\| class="wikitable"
	! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username		! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
	\|-		\|-
	\| [A][B] //B=zero matrix \|\| 10 \|\| ? \|\| 0.6 \|\| ? \|\| 2.55MP/lirtosiast		\| [A][B] //B=zero matrix \|\| 10 \|\| 13,000 \|\| 0.6 \|\| 13,000 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| [A][B] //B=identity(20 \|\| 10 \|\| ? \|\| 0.6 \|\| ? \|\| 2.55MP/lirtosiast		\| [A][B] //B=identity(20 \|\| 10 \|\| 11,800 \|\| 0.6 \|\| 11,800 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| [A][B] //B=exchange matrix \|\| 11,800 ~~\|\| 9.3~~ \|\| 0.6 \|\| 11,800 \|\| 2.55MP/lirtosiast		\| [A][B] //B=exchange matrix \|\| 10 \|\| 11,800 \|\| 0.6 \|\| 11,800 \|\| 2.55MP/lirtosiast
	\|}		\|}

lirtosiast: /* Matrix Commands */

2016-03-30T01:58:29Z

Matrix Commands

@@ Line 114: / Line 114: @@
 {| class="wikitable"
 ! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
 |-
 | [A]^^T //20x2 || 10000 || 9.3 || 0.6 || 8.7 || 2.55MP/lirtosiast
@@ Line 119: / Line 121: @@
 | [A]^^T //2x20 || 10000 || 9.4 || 0.6 || 8.8 || 2.55MP/lirtosiast
 |-
-| [A]^^T //20x20 || 1000 || 62 || 0.6 || ~62 || 2.55MP/lirtosiast
+| [A]^^T || 1000 || 62 || 0.6 || ~62 || 2.55MP/lirtosiast
 |}

lirtosiast: /* Instructions */

2016-03-30T01:46:12Z

Instructions

← Older revision		Revision as of 01:46, 30 March 2016
Line 15:		Line 15:
	Repeat checkTmr(θ		Repeat checkTmr(θ
	End		End
	For(~~𝑛,1~~,[iterations]) //sequence variable 𝑛; note the closing parenthesis.		For(𝑛1,[iterations]) //sequence variable 𝑛; note the closing parenthesis.
	//test code here		//test code here
	End		End

lirtosiast at 01:45, 30 March 2016

2016-03-30T01:45:18Z

← Older revision		Revision as of 01:45, 30 March 2016
Line 1:		Line 1:
	= Instructions =		= Instructions =

	First, write the name and model of your calculator in the table below, then use this code ~~'''with an empty line in the "test code here" space'''~~ to measure your loop overhead.		First, write the name and model of your calculator in the table below, then use this code to measure your loop overhead (without an empty line).

	Add the number of iterations you used to the "iterations" column, and [time taken]/[iterations] to the "average" column. Then subtract your loop overhead from the result and list it in the "time" column.		Add the number of iterations you used to the "iterations" column, and [time taken]/[iterations] to the "average" column. Then subtract your loop overhead from the result and list it in the "time" column.
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	\|}		\|}

	== List~~/Matrix~~ Commands ==		== List Commands ==

	Unless specified, all list/matrix elements are equal to 1, and all dimensions are equal to 20.		Unless specified, all list/matrix elements are equal to 1, and all dimensions are equal to 20.
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	\|}		\|}

			== Matrix Commands==

	When using matrix commands, remember that matrix multiplication is O(n^3). It's probably slower than other solutions for large matrices.		When using matrix commands, remember that matrix multiplication is O(n^3). It's probably slower than other solutions for large matrices.

lirtosiast: /* List/Matrix Commands */

2016-03-29T23:40:50Z

List/Matrix Commands

← Older revision		Revision as of 23:40, 29 March 2016
Line 73:		Line 73:
	\| seq(1,n,1,20 //loop var X \|\| 1000 \|\| 71 \|\| 1.1 \|\| 70 \|\| 2.55MP/lirtosiast		\| seq(1,n,1,20 //loop var X \|\| 1000 \|\| 71 \|\| 1.1 \|\| 70 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| seq(1,X,1,20 //loop var n \|\| 1000 \|\| 82 \|\| 0.6 \|\| 70 \|\| 2.55MP/lirtosiast		\| seq(1,X,1,20 //loop var n \|\| 1000 \|\| 82 \|\| 0.6 \|\| 82 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| seq(1,X,1,20 //loop var X \|\| 1000 \|\| 83 \|\| 1.1 \|\| 70 \|\| 2.55MP/lirtosiast		\| seq(1,X,1,20 //loop var X \|\| 1000 \|\| 83 \|\| 1.1 \|\| 82 \|\| 2.55MP/lirtosiast
			\|}

			seq( has a large overhead (about 3.5 ms per element), but the penalty doesn't increase by much when the expression inside the seq( is large. Vectorized list operations outside the seq( are only marginally faster than operations inside the seq(.

			{\| class="wikitable"
			! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
			\|-
			\| seq(1+1,n,1,20 \|\| 1000 \|\| 92 \|\| 0.6 \|\| 92 \|\| 2.55MP/lirtosiast
			\|-
			\| 1+seq(1,n,1,20 \|\| 1000 \|\| 92 \|\| 0.6 \|\| 92 \|\| 2.55MP/lirtosiast
			\|-
			\| seq(not(1),n,1,20 \|\| 1000 \|\| 79 \|\| 0.6 \|\| 79 \|\| 2.55MP/lirtosiast
			\|-
			\| not(seq(1,n,1,20 \|\| 1000 \|\| 76 \|\| 0.6 \|\| 76 \|\| 2.55MP/lirtosiast
	\|}		\|}

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	{\| class="wikitable"		{\| class="wikitable"
	! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username		! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
			\|-
	\| binompdf(19,0 \|\| 1000 \|\| 5 \|\| 0.6 \|\| 5 \|\| 2.55MP/lirtosiast		\| binompdf(19,0 \|\| 1000 \|\| 5 \|\| 0.6 \|\| 5 \|\| 2.55MP/lirtosiast
	\|-		\|-
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	\|}		\|}


			When using matrix commands, remember that matrix multiplication is O(n^3). It's probably slower than other solutions for large matrices.

	{\| class="wikitable"		{\| class="wikitable"

lirtosiast: /* List/Matrix Commands */

2016-03-29T23:22:32Z

List/Matrix Commands

← Older revision		Revision as of 23:22, 29 March 2016
Line 76:		Line 76:
	\|-		\|-
	\| seq(1,X,1,20 //loop var X \|\| 1000 \|\| 83 \|\| 1.1 \|\| 70 \|\| 2.55MP/lirtosiast		\| seq(1,X,1,20 //loop var X \|\| 1000 \|\| 83 \|\| 1.1 \|\| 70 \|\| 2.55MP/lirtosiast
			\|}

	binomcdf(N-1,0 is often used to construct a list of a certain length N, but binompdf( can be slightly faster. The difference is about equal to the time for a call to cumSum(. When called with a second argument that is not 0 or 1, binompdf( slows down dramatically, by a factor of 60.		binomcdf(N-1,0 is often used to construct a list of a certain length N, but binompdf( can be slightly faster. The difference is about equal to the time for a call to cumSum(. When called with a second argument that is not 0 or 1, binompdf( slows down dramatically, by a factor of 60.

lirtosiast: /* List/Matrix Commands */

2016-03-29T23:21:43Z

List/Matrix Commands

← Older revision		Revision as of 23:21, 29 March 2016
Line 35:		Line 35:

	== List/Matrix Commands ==		== List/Matrix Commands ==

			Unless specified, all list/matrix elements are equal to 1, and all dimensions are equal to 20.

	{\| class="wikitable"		{\| class="wikitable"
	! Command !! Iterations !! Average (ms) !! ~~Loop overhead~~ (ms) !! Time (ms)!! Username		! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
	\|-		\|-
	\| L1 ~~//dim=20~~\|\| 1000 \|\| 2.? \|\| 0.6 \|\| ~2 \|\| 2.55MP/lirtosiast		\| L1 \|\| 1000 \|\| 2.? \|\| 0.6 \|\| ~2 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| not(L1 ~~//dim=20~~ \|\| 1000 \|\| 9.? \|\| 0.6 \|\| ~9 \|\| 2.55MP/lirtosiast		\| not(L1 \|\| 1000 \|\| 9.? \|\| 0.6 \|\| ~9 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| L1+0 ~~//dim=20~~ \|\| 1000 \|\| 20 \|\| 0.6 \|\| ~20 \|\| 2.55MP/lirtosiast		\| L1+0 \|\| 1000 \|\| 20 \|\| 0.6 \|\| ~20 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| cumSum(L1 ~~//dim=20~~ \|\| 1000 \|\| 19 \|\| 0.6 \|\| ~19 \|\| 2.55MP/lirtosiast		\| cumSum(L1 \|\| 1000 \|\| 19 \|\| 0.6 \|\| ~19 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| DeltaList(L1 ~~//dim=20~~ \|\| 1000 \|\| 26 \|\| 0.6 \|\| ~26 \|\| 2.55MP/lirtosiast		\| DeltaList(L1 \|\| 1000 \|\| 26 \|\| 0.6 \|\| ~26 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| augment(L1,L1 ~~//dim=20~~ \|\| 10000 \|\| 9.4 \|\| 0.6 \|\| 8.8 \|\| 2.55MP/lirtosiast		\| augment(L1,L1 \|\| 10000 \|\| 9.4 \|\| 0.6 \|\| 8.8 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| augment(L1,{1 ~~//dim=20~~ \|\| 10000 \|\| 7.7 \|\| 0.6 \|\| 7.1 \|\| 2.55MP/lirtosiast		\| augment(L1,{1 \|\| 10000 \|\| 7.7 \|\| 0.6 \|\| 7.1 \|\| 2.55MP/lirtosiast
	\|-		\|-
	\| augment({1},L1 //dim=20 \|\| 10000 \|\| 7.7 \|\| 0.6 \|\| 7.1 \|\| 2.55MP/lirtosiast		\| augment({1},L1 //dim=20 \|\| 10000 \|\| 7.7 \|\| 0.6 \|\| 7.1 \|\| 2.55MP/lirtosiast
Line 61:		Line 63:
	\| Fill(1,L1 //dim=20 \|\| 10000 \|\| 3.9 \|\| 0.6 \|\| 3.3 \|\| 2.55MP/lirtosiast		\| Fill(1,L1 //dim=20 \|\| 10000 \|\| 3.9 \|\| 0.6 \|\| 3.3 \|\| 2.55MP/lirtosiast
	\|}		\|}

			Below we can see that using the same variable for the seq( variable as the For( variable doesn't slow anything down. The value of the variable before seq( was called is restored in a constant amount of time.

			{\| class="wikitable"
			! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
			\|-
			\| seq(1,n,1,20 //loop var n \|\| 1000 \|\| 70 \|\| 0.6 \|\| 70 \|\| 2.55MP/lirtosiast
			\|-
			\| seq(1,n,1,20 //loop var X \|\| 1000 \|\| 71 \|\| 1.1 \|\| 70 \|\| 2.55MP/lirtosiast
			\|-
			\| seq(1,X,1,20 //loop var n \|\| 1000 \|\| 82 \|\| 0.6 \|\| 70 \|\| 2.55MP/lirtosiast
			\|-
			\| seq(1,X,1,20 //loop var X \|\| 1000 \|\| 83 \|\| 1.1 \|\| 70 \|\| 2.55MP/lirtosiast

			binomcdf(N-1,0 is often used to construct a list of a certain length N, but binompdf( can be slightly faster. The difference is about equal to the time for a call to cumSum(. When called with a second argument that is not 0 or 1, binompdf( slows down dramatically, by a factor of 60.

			{\| class="wikitable"
			! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
			\| binompdf(19,0 \|\| 1000 \|\| 5 \|\| 0.6 \|\| 5 \|\| 2.55MP/lirtosiast
			\|-
			\| binomcdf(19,0 \|\| 1000 \|\| 20 \|\| 0.6 \|\| 20 \|\| 2.55MP/lirtosiast
			\|-
			\| 1 or binompdf(19,0 \|\| 1000 \|\| 16 \|\| 0.6 \|\| 16 \|\| 2.55MP/lirtosiast
			\|-
			\| binompdf(19,1 \|\| 1000 \|\| 5 \|\| 0.6 \|\| 5 \|\| 2.55MP/lirtosiast
			\|-
			\| binompdf(19,.5 \|\| 1000 \|\| 296 \|\| 0.6 \|\| 296 \|\| 2.55MP/lirtosiast
			\|}


	{\| class="wikitable"		{\| class="wikitable"
	! Command !! Iterations !! Average (ms) !! ~~Loop overhead~~ (ms) !! Time (ms)!! Username		! Command !! Iterations !! Average (ms) !! Overhead (ms) !! Time (ms)!! Username
	\|-		\|-
	\| [A]^^T //20x2 \|\| 10000 \|\| 9.3 \|\| 0.6 \|\| 8.7 \|\| 2.55MP/lirtosiast		\| [A]^^T //20x2 \|\| 10000 \|\| 9.3 \|\| 0.6 \|\| 8.7 \|\| 2.55MP/lirtosiast