{"id":18576,"date":"2016-10-20T17:04:14","date_gmt":"2016-10-20T16:04:14","guid":{"rendered":"https:\/\/fortran.uk\/?page_id=18576"},"modified":"2017-04-28T11:07:35","modified_gmt":"2017-04-28T10:07:35","slug":"polyhedron-benchmarks-amdlinux64-sept-2015","status":"publish","type":"page","link":"https:\/\/fortran.uk\/historic-tables\/polyhedron-benchmarks-amdlinux64-sept-2015\/","title":{"rendered":"Polyhedron Benchmarks (AMD+Linux64 Sept 2015)"},"content":{"rendered":"\n\n\n
<\/td>\n\n

Linux\/64 on AMD Processor<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/td>\nAbsoft<\/i><\/b>
\n15.0.2<\/small><\/td>\n		Absoft(AP)<\/i><\/b>
\n15.0.2<\/small><\/td>\n		gfortran<\/i><\/b>
\n5.2.0<\/small><\/td>\n		Intel<\/i><\/b>
\n16.0<\/small><\/td>\n		Intel(AP)<\/i><\/b>
\n16.0<\/small><\/td>\n		NAG<\/i><\/b>
\n6.0<\/small><\/td>\n		Oracle<\/i><\/b>
\n12.4<\/small><\/td>\n		PGI<\/i><\/b>
\n15.7<\/small><\/td>\n		open64<\/i><\/b>
\n4.5.2.1<\/small><\/td>\n<\/tr>\n
AC<\/i><\/b><\/strong><\/em><\/td>\n7.50<\/td>\n7.46<\/td>\n8.54<\/td>\n6.86<\/td>\n6.87<\/td>\n20.86<\/td>\n19.68<\/td>\n8.72<\/td>\n7.32<\/td>\n<\/tr>\n
AERMOD<\/i><\/b><\/strong><\/em><\/td>\n16.65<\/td>\n17.10<\/td>\n23.35<\/td>\n16.71<\/td>\n17.23<\/td>\n22.89<\/td>\n15.40<\/td>\n17.25<\/td>\n24.19<\/td>\n<\/tr>\n
AIR<\/i><\/b><\/strong><\/em><\/td>\n4.54<\/td>\n3.12<\/td>\n5.24<\/td>\n4.29<\/td>\n2.17<\/td>\n6.22<\/td>\n4.69<\/td>\n5.68<\/td>\n4.83<\/td>\n<\/tr>\n
CAPACITA<\/i><\/b><\/strong><\/em><\/td>\n32.93<\/td>\n33.41<\/td>\n38.46<\/td>\n34.05<\/td>\n34.23<\/td>\n40.38<\/td>\n39.89<\/td>\n30.30<\/td>\n31.64<\/td>\n<\/tr>\n
CHANNEL2<\/i><\/b><\/strong><\/em><\/td>\n137.72<\/td>\n129.71<\/td>\n136.89<\/td>\n141.50<\/td>\n114.96<\/td>\n212.97<\/td>\n142.31<\/td>\n139.51<\/td>\n188.36<\/td>\n<\/tr>\n
DODUC<\/i><\/b><\/strong><\/em><\/td>\n26.38<\/td>\n26.33<\/td>\n25.64<\/td>\n21.62<\/td>\n21.64<\/td>\n28.08<\/td>\n23.24<\/td>\n25.36<\/td>\n25.01<\/td>\n<\/tr>\n
FATIGUE2<\/i><\/b><\/strong><\/em><\/td>\n80.51<\/td>\n84.41<\/td>\n83.77<\/td>\n76.57<\/td>\n73.42<\/td>\n120.49<\/td>\n128.18<\/td>\n114.84<\/td>\n100.77<\/td>\n<\/tr>\n
GAS_DYN2<\/i><\/b><\/strong><\/em><\/td>\n113.02<\/td>\n137.03<\/td>\n132.56<\/td>\n97.83<\/td>\n104.09<\/td>\n205.98<\/td>\n118.38<\/td>\n149.18<\/td>\n104.03<\/td>\n<\/tr>\n
INDUCT2<\/i><\/b><\/strong><\/em><\/td>\n96.77<\/td>\n55.30<\/td>\n102.67<\/td>\n109.76<\/td>\n45.01<\/td>\n193.00<\/td>\n188.17<\/td>\n197.23<\/td>\n166.37<\/td>\n<\/tr>\n
LINPK<\/i><\/b><\/strong><\/em><\/td>\n9.04<\/td>\n9.09<\/td>\n8.22<\/td>\n9.45<\/td>\n9.46<\/td>\n9.91<\/td>\n9.88<\/td>\n9.94<\/td>\n10.55<\/td>\n<\/tr>\n
MDBX<\/i><\/b><\/strong><\/em><\/td>\n12.98<\/td>\n12.52<\/td>\n12.72<\/td>\n10.52<\/td>\n10.44<\/td>\n12.74<\/td>\n12.06<\/td>\n12.98<\/td>\n12.32<\/td>\n<\/tr>\n
MP_PROP_DESIGN<\/i><\/b><\/strong><\/em><\/td>\n134.25<\/td>\n70.83<\/td>\n263.03<\/td>\n110.53<\/td>\n34.15<\/td>\n360.59<\/td>\n207.02<\/td>\n125.39<\/td>\n140.57<\/td>\n<\/tr>\n
NF<\/i><\/b><\/strong><\/em><\/td>\n12.04<\/td>\n12.02<\/td>\n10.87<\/td>\n11.25<\/td>\n11.31<\/td>\n13.96<\/td>\n12.08<\/td>\n12.13<\/td>\n11.73<\/td>\n<\/tr>\n
PROTEIN<\/i><\/b><\/strong><\/em><\/td>\n30.35<\/td>\n30.85<\/td>\n31.73<\/td>\n30.30<\/td>\n30.35<\/td>\n34.60<\/td>\n31.23<\/td>\n36.02<\/td>\n30.46<\/td>\n<\/tr>\n
RNFLOW<\/i><\/b><\/strong><\/em><\/td>\n17.30<\/td>\n19.86<\/td>\n20.68<\/td>\n18.07<\/td>\n18.27<\/td>\n22.16<\/td>\n26.59<\/td>\n22.61<\/td>\n25.44<\/td>\n<\/tr>\n
TEST_FPU2<\/i><\/b><\/strong><\/em><\/td>\n98.76<\/td>\n88.34<\/td>\n86.13<\/td>\n83.44<\/td>\n77.35<\/td>\n116.77<\/td>\n102.55<\/td>\n94.03<\/td>\n90.66<\/td>\n<\/tr>\n
TFFT2<\/i><\/b><\/strong><\/em><\/td>\n157.74<\/td>\n155.27<\/td>\n112.31<\/td>\n157.57<\/td>\n160.14<\/td>\n159.98<\/td>\n156.42<\/td>\n161.81<\/td>\n159.53<\/td>\n<\/tr>\n
<\/td>\n<\/tr>\n
Geometric Mean<\/b><\/i><\/strong><\/td>\n33.69<\/td>\n31.09<\/td>\n36.13<\/td>\n31.94<\/td>\n26.86<\/td>\n47.44<\/td>\n40.50<\/td>\n38.10<\/td>\n37.34<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n
Compiler Switches<\/strong><\/td>\n<\/tr>\n
Absoft<\/strong><\/td>\naf90 -m64 -O4 -speed_math=10 -march=barcelona -xINTEGER<\/td>\n<\/tr>\n
Absoft(AP)<\/strong><\/td>\naf90 -m64 -O5 -speed_math=10 -march=barcelona -xINTEGER
\n(These settings enable auto-parallelization, see below)<\/td>\n<\/tr>\n
gfortran<\/strong><\/td>\ngfortran -ffast-math -funroll-loops \u00a0–param max-unroll-times=2 -Ofast -march=<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

ative<\/td>\n<\/tr>\n

Intel<\/strong><\/td>\nifort -fast -ipo<\/td>\n<\/tr>\n
Intel(AP)<\/strong><\/td>\nifort -fast -parallel -ipo (These settings enable auto-parallelization, see below)<\/td>\n<\/tr>\n
NAG<\/strong><\/td>\nnagfor -O4 -s -v -V<\/td>\n<\/tr>\n
PGI<\/strong><\/td>\npgf90 -V -fast -Mipa=fast,inline -Msmartalloc -Mfprelaxed -Mstack_arrays<\/td>\n<\/tr>\n
Oracle<\/strong><\/td>\nsunf95 -fast -xtarget=native -m64<\/td>\n<\/tr>\n
Open64<\/strong><\/td>\nopenf95 -Ofast<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n
Notes<\/strong><\/span><\/td>\n<\/tr>\n
All figures are execution times in seconds – measured on a machine with an AMD Phenom II X4 955 processor (3.2 GHz), with 8GBytes memory, running Linux Mint 17.1. Each figure is the average over at least 10 runs (many more for some). Measurement error is typically <1%. Green cells highlight figures within 10% of the fastest. Red cells indicate figures which are more than 150% of the fastest.\u00a0 So far as possible, we have used the compiler switches which give the best overall results. We have not attempted to tune individual benchmarks, and, in particular cases, different switch settings may give better results. The settings used for the Intel and Absoft compilers enable autoparallelization. Autoparallelization settings are not used on any other compilers because we found that they produced no significant performance benefits on this benchmark set.\u00a0 Thanks are due to Jos Bergervoet for permission to use his CAPACITA benchmark, to Quetzal Associates for permission to use their CHANNEL, FATIGUE, GAS_DYN, INDUCT, PROTEIN and RNFLOW benchmarks, to David Frank for his TEST_FPU benchmark, to Anthony Falzone for the use of MP_PROP_DESIGN, and to Ted Addison of McVehil-Monnett Associates for permission to use AERMOD, an air quality model used by the US Environmental Protection Agency.\u00a0 All the benchmarks have been modified slightly to fit into our benchmarking harness.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Linux\/64 on AMD Processor Absoft 15.0.2 Absoft(AP) 15.0.2 gfortran 5.2.0 Intel 16.0 Intel(AP) 16.0 NAG 6.0 Oracle 12.4 PGI 15.7 open64 4.5.2.1 AC 7.50 7.46 8.54 6.86 6.87 20.86 19.68 8.72 7.32 AERMOD 16.65 17.10 23.35 16.71 17.23 22.89 15.40 17.25 24.19 AIR 4.54 3.12 5.24 4.29 2.17 6.22 4.69 5.68 4.83 CAPACITA 32.93 33.41 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":18364,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"yoast_head":"\nPolyhedron Benchmarks (AMD+Linux64 Sept 2015) - Fortran UK<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fortran.uk\/historic-tables\/polyhedron-benchmarks-amdlinux64-sept-2015\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Polyhedron Benchmarks (AMD+Linux64 Sept 2015) - 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