chore: add additional numbers

Makefile

@@ -173,11 +173,13 @@ profile_scscan: profile_all_s_fp16_scscan
 profile_scan_single_cube: profile_all_s_fp16_scan_single_cube
 
 profile_compress_paper:
+	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench compress --s 128 --density 0.01 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench compress --s 128 --density 0.1 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench compress --s 128 --density 0.2 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench compress --s 128 --density 0.5 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench compress --s 128 --density 0.8 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench compress --s 128 --density 0.9 --dtype fp16
+	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench compress --s 128 --density 0.99 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench masked_select --s 128 --density 0.1 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench masked_select --s 128 --density 0.2 --dtype fp16
 	python3 ${PROFILING_SCRIPTS_PATH}/profile_tcuscan_ops.py --bench masked_select --s 128 --density 0.5 --dtype fp16

bench_results_compress_128_0.01_fp16.csv

@@ -0,0 +1,21 @@
+operator,dtype,size,density,outputsize,time_us
+compress_128_0.01_fp16,fp16,327680,0.01,3264,210.42
+compress_128_0.01_fp16,fp16,5570560,0.01,55670,255.68
+compress_128_0.01_fp16,fp16,10813440,0.01,107979,316.15
+compress_128_0.01_fp16,fp16,16056320,0.01,159749,386.88
+compress_128_0.01_fp16,fp16,21299200,0.01,213220,440.74
+compress_128_0.01_fp16,fp16,26542080,0.01,265827,485.60
+compress_128_0.01_fp16,fp16,31784960,0.01,317505,537.38
+compress_128_0.01_fp16,fp16,37027840,0.01,369728,577.41
+compress_128_0.01_fp16,fp16,42270720,0.01,422478,604.43
+compress_128_0.01_fp16,fp16,47513600,0.01,474449,633.27
+compress_128_0.01_fp16,fp16,52756480,0.01,528155,672.62
+compress_128_0.01_fp16,fp16,57999360,0.01,578832,704.46
+compress_128_0.01_fp16,fp16,63242240,0.01,632939,739.50
+compress_128_0.01_fp16,fp16,68485120,0.01,685455,782.46
+compress_128_0.01_fp16,fp16,73728000,0.01,738248,819.59
+compress_128_0.01_fp16,fp16,78970880,0.01,789666,851.09
+compress_128_0.01_fp16,fp16,84213760,0.01,841957,888.61
+compress_128_0.01_fp16,fp16,89456640,0.01,895428,908.09
+compress_128_0.01_fp16,fp16,94699520,0.01,945487,950.58
+compress_128_0.01_fp16,fp16,99942400,0.01,1000738,989.26

bench_results_compress_128_0.1_fp16.csv

@@ -0,0 +1,21 @@
+operator,dtype,size,density,outputsize,time_us
+compress_128_0.1_fp16,fp16,327680,0.1,32789,222.96
+compress_128_0.1_fp16,fp16,5570560,0.1,557118,260.29
+compress_128_0.1_fp16,fp16,10813440,0.1,1081525,316.50
+compress_128_0.1_fp16,fp16,16056320,0.1,1604886,380.34
+compress_128_0.1_fp16,fp16,21299200,0.1,2130381,446.19
+compress_128_0.1_fp16,fp16,26542080,0.1,2655877,497.46
+compress_128_0.1_fp16,fp16,31784960,0.1,3176702,542.89
+compress_128_0.1_fp16,fp16,37027840,0.1,3702629,583.56
+compress_128_0.1_fp16,fp16,42270720,0.1,4227261,624.01
+compress_128_0.1_fp16,fp16,47513600,0.1,4753607,656.21
+compress_128_0.1_fp16,fp16,52756480,0.1,5277747,696.09
+compress_128_0.1_fp16,fp16,57999360,0.1,5794772,739.43
+compress_128_0.1_fp16,fp16,63242240,0.1,6323460,783.00
+compress_128_0.1_fp16,fp16,68485120,0.1,6847723,824.07
+compress_128_0.1_fp16,fp16,73728000,0.1,7375326,865.25
+compress_128_0.1_fp16,fp16,78970880,0.1,7900530,907.47
+compress_128_0.1_fp16,fp16,84213760,0.1,8422212,954.39
+compress_128_0.1_fp16,fp16,89456640,0.1,8947539,995.49
+compress_128_0.1_fp16,fp16,94699520,0.1,9466954,1025.43
+compress_128_0.1_fp16,fp16,99942400,0.1,9993589,1061.50

bench_results_compress_128_0.2_fp16.csv

@@ -0,0 +1,21 @@
+operator,dtype,size,density,outputsize,time_us
+compress_128_0.2_fp16,fp16,327680,0.2,65455,217.12
+compress_128_0.2_fp16,fp16,5570560,0.2,1111860,258.61
+compress_128_0.2_fp16,fp16,10813440,0.2,2163912,320.90
+compress_128_0.2_fp16,fp16,16056320,0.2,3212100,391.02
+compress_128_0.2_fp16,fp16,21299200,0.2,4260610,450.77
+compress_128_0.2_fp16,fp16,26542080,0.2,5308100,507.02
+compress_128_0.2_fp16,fp16,31784960,0.2,6359520,544.31
+compress_128_0.2_fp16,fp16,37027840,0.2,7405267,584.64
+compress_128_0.2_fp16,fp16,42270720,0.2,8454686,626.68
+compress_128_0.2_fp16,fp16,47513600,0.2,9503175,663.95
+compress_128_0.2_fp16,fp16,52756480,0.2,10554368,707.96
+compress_128_0.2_fp16,fp16,57999360,0.2,11599914,762.05
+compress_128_0.2_fp16,fp16,63242240,0.2,12645503,798.08
+compress_128_0.2_fp16,fp16,68485120,0.2,13703968,841.02
+compress_128_0.2_fp16,fp16,73728000,0.2,14746419,885.35
+compress_128_0.2_fp16,fp16,78970880,0.2,15786819,933.06
+compress_128_0.2_fp16,fp16,84213760,0.2,16850331,976.63
+compress_128_0.2_fp16,fp16,89456640,0.2,17897883,1019.83
+compress_128_0.2_fp16,fp16,94699520,0.2,18939562,1070.36
+compress_128_0.2_fp16,fp16,99942400,0.2,19989637,1111.00

bench_results_compress_128_0.5_fp16.csv

@@ -0,0 +1,21 @@
+operator,dtype,size,density,outputsize,time_us
+compress_128_0.5_fp16,fp16,327680,0.5,163843,213.28
+compress_128_0.5_fp16,fp16,5570560,0.5,2785837,269.30
+compress_128_0.5_fp16,fp16,10813440,0.5,5407841,331.45
+compress_128_0.5_fp16,fp16,16056320,0.5,8028299,403.55
+compress_128_0.5_fp16,fp16,21299200,0.5,10648217,467.85
+compress_128_0.5_fp16,fp16,26542080,0.5,13271454,521.18
+compress_128_0.5_fp16,fp16,31784960,0.5,15893038,558.39
+compress_128_0.5_fp16,fp16,37027840,0.5,18511582,598.77
+compress_128_0.5_fp16,fp16,42270720,0.5,21136727,646.28
+compress_128_0.5_fp16,fp16,47513600,0.5,23757161,694.67
+compress_128_0.5_fp16,fp16,52756480,0.5,26373181,746.02
+compress_128_0.5_fp16,fp16,57999360,0.5,28993855,802.23
+compress_128_0.5_fp16,fp16,63242240,0.5,31622407,842.28
+compress_128_0.5_fp16,fp16,68485120,0.5,34242030,886.87
+compress_128_0.5_fp16,fp16,73728000,0.5,36871459,942.99
+compress_128_0.5_fp16,fp16,78970880,0.5,39489418,990.87
+compress_128_0.5_fp16,fp16,84213760,0.5,42108961,1031.48
+compress_128_0.5_fp16,fp16,89456640,0.5,44726049,1084.93
+compress_128_0.5_fp16,fp16,94699520,0.5,47349990,1132.55
+compress_128_0.5_fp16,fp16,99942400,0.5,49972231,1177.71

bench_results_compress_128_0.8_fp16.csv

@@ -0,0 +1,21 @@
+operator,dtype,size,density,outputsize,time_us
+compress_128_0.8_fp16,fp16,327680,0.8,261716,225.92
+compress_128_0.8_fp16,fp16,5570560,0.8,4456771,270.91
+compress_128_0.8_fp16,fp16,10813440,0.8,8651159,345.55
+compress_128_0.8_fp16,fp16,16056320,0.8,12846562,417.33
+compress_128_0.8_fp16,fp16,21299200,0.8,17037790,487.58
+compress_128_0.8_fp16,fp16,26542080,0.8,21234285,532.18
+compress_128_0.8_fp16,fp16,31784960,0.8,25428080,577.56
+compress_128_0.8_fp16,fp16,37027840,0.8,29619534,622.78
+compress_128_0.8_fp16,fp16,42270720,0.8,33814208,692.84
+compress_128_0.8_fp16,fp16,47513600,0.8,38010293,747.10
+compress_128_0.8_fp16,fp16,52756480,0.8,42210103,794.14
+compress_128_0.8_fp16,fp16,57999360,0.8,46396462,862.57
+compress_128_0.8_fp16,fp16,63242240,0.8,50595481,916.01
+compress_128_0.8_fp16,fp16,68485120,0.8,54789126,961.46
+compress_128_0.8_fp16,fp16,73728000,0.8,58982366,1013.23
+compress_128_0.8_fp16,fp16,78970880,0.8,63184762,1074.37
+compress_128_0.8_fp16,fp16,84213760,0.8,67371108,1131.25
+compress_128_0.8_fp16,fp16,89456640,0.8,71564443,1182.98
+compress_128_0.8_fp16,fp16,94699520,0.8,75755909,1229.00
+compress_128_0.8_fp16,fp16,99942400,0.8,79952605,1283.11

bench_results_compress_128_0.99_fp16.csv

@@ -0,0 +1,21 @@
+operator,dtype,size,density,outputsize,time_us
+compress_128_0.99_fp16,fp16,327680,0.99,324453,209.23
+compress_128_0.99_fp16,fp16,5570560,0.99,5514861,272.59
+compress_128_0.99_fp16,fp16,10813440,0.99,10705723,342.79
+compress_128_0.99_fp16,fp16,16056320,0.99,15895671,420.88
+compress_128_0.99_fp16,fp16,21299200,0.99,21086274,482.25
+compress_128_0.99_fp16,fp16,26542080,0.99,26276436,538.96
+compress_128_0.99_fp16,fp16,31784960,0.99,31466953,589.99
+compress_128_0.99_fp16,fp16,37027840,0.99,36657112,655.47
+compress_128_0.99_fp16,fp16,42270720,0.99,41848773,689.32
+compress_128_0.99_fp16,fp16,47513600,0.99,47038689,764.11
+compress_128_0.99_fp16,fp16,52756480,0.99,52228626,825.08
+compress_128_0.99_fp16,fp16,57999360,0.99,57418592,873.85
+compress_128_0.99_fp16,fp16,63242240,0.99,62610053,938.69
+compress_128_0.99_fp16,fp16,68485120,0.99,67800396,994.50
+compress_128_0.99_fp16,fp16,73728000,0.99,72991290,1034.91
+compress_128_0.99_fp16,fp16,78970880,0.99,78181821,1088.06
+compress_128_0.99_fp16,fp16,84213760,0.99,83371165,1159.84
+compress_128_0.99_fp16,fp16,89456640,0.99,88562365,1208.13
+compress_128_0.99_fp16,fp16,94699520,0.99,93752582,1262.92
+compress_128_0.99_fp16,fp16,99942400,0.99,98943905,1318.64

bench_results_compress_128_0.9_fp16.csv

@@ -0,0 +1,21 @@
+operator,dtype,size,density,outputsize,time_us
+compress_128_0.9_fp16,fp16,327680,0.9,294992,206.31
+compress_128_0.9_fp16,fp16,5570560,0.9,5012873,267.13
+compress_128_0.9_fp16,fp16,10813440,0.9,9732232,344.17
+compress_128_0.9_fp16,fp16,16056320,0.9,14450039,428.24
+compress_128_0.9_fp16,fp16,21299200,0.9,19168338,492.68
+compress_128_0.9_fp16,fp16,26542080,0.9,23888342,527.34
+compress_128_0.9_fp16,fp16,31784960,0.9,28605784,578.75
+compress_128_0.9_fp16,fp16,37027840,0.9,33323936,641.55
+compress_128_0.9_fp16,fp16,42270720,0.9,38045326,706.67
+compress_128_0.9_fp16,fp16,47513600,0.9,42760859,766.08
+compress_128_0.9_fp16,fp16,52756480,0.9,47479947,820.39
+compress_128_0.9_fp16,fp16,57999360,0.9,52202540,868.96
+compress_128_0.9_fp16,fp16,63242240,0.9,56921129,923.85
+compress_128_0.9_fp16,fp16,68485120,0.9,61637260,980.22
+compress_128_0.9_fp16,fp16,73728000,0.9,66359596,1034.41
+compress_128_0.9_fp16,fp16,78970880,0.9,71069334,1092.97
+compress_128_0.9_fp16,fp16,84213760,0.9,75790127,1124.17
+compress_128_0.9_fp16,fp16,89456640,0.9,80512304,1195.76
+compress_128_0.9_fp16,fp16,94699520,0.9,85231186,1242.83
+compress_128_0.9_fp16,fp16,99942400,0.9,89942921,1298.68