| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315 | ################### Performance Model Version45##################### COMBs# number of combinations9##################### COMB_8# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)0##################### DEV_0# device id 0##################### DEV_0# number of cores 1########### number of implementations1###### Model for cpu0_impl0 (Comb8)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		ncea37d6d	409600         	0.000000e+00   	4.307978e+03   	6.474305e+01   	1.249314e+05   	5.383232e+08   	29afdd228b	1638400        	0.000000e+00   	3.550524e+04   	4.451382e+02   	3.550524e+05   	1.260821e+10   	10617e5fe6	3686400        	0.000000e+00   	1.169735e+05   	9.368471e+02   	1.169735e+06   	1.368368e+11   	10##################### COMB_3# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 0##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda0_impl0 (Comb3)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		ncea37d6d	409600         	0.000000e+00   	1.140547e+04   	1.799023e+03   	1.140547e+05   	1.333212e+09   	10afdd228b	1638400        	0.000000e+00   	2.728447e+04   	8.307498e+02   	2.728447e+05   	7.451326e+09   	10617e5fe6	3686400        	0.000000e+00   	6.234962e+04   	7.670296e+03   	6.858458e+05   	4.340939e+10   	11##################### COMB_2# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 5##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda5_impl0 (Comb2)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		nafdd228b	1638400        	0.000000e+00   	3.084154e+04   	4.741973e+03   	3.084154e+05   	9.736872e+09   	10cea37d6d	409600         	0.000000e+00   	1.194801e+04   	1.916839e+03   	1.194801e+05   	1.464291e+09   	10617e5fe6	3686400        	0.000000e+00   	6.590141e+04   	1.170188e+04   	6.590141e+05   	4.479930e+10   	10##################### COMB_1# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 6##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda6_impl0 (Comb1)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		n617e5fe6	3686400        	0.000000e+00   	7.169178e+04   	1.134864e+04   	7.886096e+05   	5.795353e+10   	11cea37d6d	409600         	0.000000e+00   	1.144166e+04   	1.161786e+03   	1.144166e+05   	1.322613e+09   	10afdd228b	1638400        	0.000000e+00   	2.872444e+04   	2.010264e+03   	3.159688e+05   	9.120481e+09   	11##################### COMB_0# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 4##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda4_impl0 (Comb0)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		ncea37d6d	409600         	0.000000e+00   	1.150326e+04   	1.434617e+03   	1.150326e+05   	1.343832e+09   	10afdd228b	1638400        	0.000000e+00   	3.088151e+04   	4.858348e+03   	3.088151e+05   	9.772711e+09   	10617e5fe6	3686400        	0.000000e+00   	6.102500e+04   	7.308309e+03   	6.102500e+05   	3.777463e+10   	10##################### COMB_4# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 7##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda7_impl0 (Comb4)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		n617e5fe6	3686400        	0.000000e+00   	5.751510e+04   	2.006299e+03   	6.901812e+05   	3.974415e+10   	12cea37d6d	409600         	0.000000e+00   	1.125363e+04   	1.219431e+03   	1.125363e+05   	1.281312e+09   	10afdd228b	1638400        	0.000000e+00   	3.238968e+04   	5.459084e+03   	3.238968e+05   	1.078893e+10   	10##################### COMB_6# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 3##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda3_impl0 (Comb6)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		nafdd228b	1638400        	0.000000e+00   	2.926764e+04   	3.325362e+03   	3.219440e+05   	9.544181e+09   	11cea37d6d	409600         	0.000000e+00   	1.088648e+04   	1.129883e+03   	1.088648e+05   	1.197920e+09   	10617e5fe6	3686400        	0.000000e+00   	6.506731e+04   	1.183046e+04   	8.458750e+05   	5.685829e+10   	13##################### COMB_5# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 1##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda1_impl0 (Comb5)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		nafdd228b	1638400        	0.000000e+00   	2.775893e+04   	1.476662e+03   	3.331071e+05   	9.272862e+09   	12cea37d6d	409600         	0.000000e+00   	1.026126e+04   	8.160679e+01   	1.026126e+05   	1.053001e+09   	10617e5fe6	3686400        	0.000000e+00   	6.215917e+04   	1.023772e+04   	6.215917e+05   	3.968573e+10   	10##################### COMB_7# number of types devices1##################### DEV_0# device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)1##################### DEV_0# device id 2##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda2_impl0 (Comb7)# number of entries3# sumlnx	sumlnx2		sumlny		sumlnxlny	alpha		beta		n	minx		maxx0.000000e+00   	0.000000e+00   	0.000000e+00   	0.000000e+00   	nan            	nan            	0	0              	0              # a		b		cnan            	nan            	nan            # not multiple-regression-base0# hash		size		flops		mean (us)	dev (us)	sum		sum2		ncea37d6d	409600         	0.000000e+00   	1.022286e+04   	3.601879e+01   	1.022286e+05   	1.045081e+09   	10afdd228b	1638400        	0.000000e+00   	2.891317e+04   	4.592264e+03   	2.891317e+05   	8.570604e+09   	10617e5fe6	3686400        	0.000000e+00   	5.724831e+04   	3.045025e+03   	7.442280e+05   	4.272633e+10   	13
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