| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184 | ################### Performance Model Version45##################### COMBs# number of combinations5##################### COMB_4# 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 (Comb4)# number of entries4# 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		n25ebb669	8294400        	0.000000e+00   	4.111343e+05   	7.639666e+04   	4.111343e+06   	1.748679e+12   	10afdd228b	1638400        	0.000000e+00   	2.923093e+04   	1.278718e+03   	5.553877e+05   	1.626557e+10   	19cea37d6d	409600         	0.000000e+00   	4.037068e+03   	3.335771e+02   	2.906689e+05   	1.181462e+09   	72617e5fe6	3686400        	0.000000e+00   	1.029624e+05   	6.177928e+03   	1.029624e+06   	1.063943e+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 3##################### DEV_0# number of cores 1########### number of implementations1###### Model for cuda3_impl0 (Comb3)# number of entries4# 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   	9.866251e+03   	7.665217e+02   	9.866251e+04   	9.793047e+08   	10afdd228b	1638400        	0.000000e+00   	2.088164e+04   	1.502169e+03   	4.176328e+05   	8.765989e+09   	20617e5fe6	3686400        	0.000000e+00   	4.153583e+04   	9.473225e+02   	9.968599e+05   	4.142694e+10   	2425ebb669	8294400        	0.000000e+00   	9.378398e+04   	2.901838e+03   	1.594328e+06   	1.496655e+11   	17##################### COMB_2# 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 (Comb2)# number of entries4# 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		n25ebb669	8294400        	0.000000e+00   	9.434448e+04   	6.197321e+03   	2.075578e+06   	1.966643e+11   	22afdd228b	1638400        	0.000000e+00   	2.242688e+04   	2.707726e+03   	3.139763e+05   	7.144153e+09   	14cea37d6d	409600         	0.000000e+00   	9.238189e+03   	1.713378e+02   	9.238189e+04   	8.537349e+08   	10617e5fe6	3686400        	0.000000e+00   	4.357190e+04   	5.271768e+03   	7.842942e+05   	3.467343e+10   	18##################### COMB_1# 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 (Comb1)# number of entries4# 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		n25ebb669	8294400        	0.000000e+00   	9.395404e+04   	4.337001e+03   	1.973035e+06   	1.857696e+11   	21afdd228b	1638400        	0.000000e+00   	2.096495e+04   	7.732458e+02   	3.773690e+05   	7.922284e+09   	18cea37d6d	409600         	0.000000e+00   	9.471831e+03   	5.475075e+02   	9.471831e+04   	9.001535e+08   	10617e5fe6	3686400        	0.000000e+00   	4.647825e+04   	9.283373e+03   	5.577390e+05   	2.695691e+10   	12##################### COMB_0# 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 (Comb0)# number of entries4# 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		n25ebb669	8294400        	0.000000e+00   	9.896522e+04   	1.438963e+04   	1.187583e+06   	1.200141e+11   	12afdd228b	1638400        	0.000000e+00   	2.172039e+04   	1.567348e+03   	2.823650e+05   	6.165013e+09   	13cea37d6d	409600         	0.000000e+00   	9.338877e+03   	3.249828e+02   	9.338877e+04   	8.732025e+08   	10617e5fe6	3686400        	0.000000e+00   	4.258012e+04   	2.921691e+03   	8.090223e+05   	3.461046e+10   	19
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