GCE c3d-standard-60

amazon testing on Ubuntu 22.04 via the Phoronix Test Suite.

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Timed Code Compilation 3 Tests
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c3d-standard-60 AMD Genoa
October 03 2023
  10 Hours, 30 Minutes
t2d-standard-60 AMD Milan
October 03 2023
  13 Hours, 23 Minutes
c6g.16xlarge
October 05 2023
  9 Hours, 27 Minutes
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  11 Hours, 7 Minutes

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GCE c3d-standard-60 Suite 1.0.0 System Test suite extracted from GCE c3d-standard-60. pts/openssl-3.1.0 sha256 Algorithm: SHA256 pts/openssl-3.1.0 sha512 Algorithm: SHA512 pts/openssl-3.1.0 -evp chacha20 Algorithm: ChaCha20 pts/openssl-3.1.0 -evp aes-128-gcm Algorithm: AES-128-GCM pts/openssl-3.1.0 -evp aes-256-gcm Algorithm: AES-256-GCM pts/openssl-3.1.0 -evp chacha20-poly1305 Algorithm: ChaCha20-Poly1305 pts/amg-1.1.0 pts/nekrs-1.1.0 kershaw kershaw.par Input: Kershaw pts/nekrs-1.1.0 turbPipePeriodic turbPipe.par Input: TurboPipe Periodic pts/openvino-1.3.0 -m models/intel/face-detection-0206/FP16/face-detection-0206.xml -d CPU Model: Face Detection FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/person-detection-0303/FP16/person-detection-0303.xml -d CPU Model: Person Detection FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/person-detection-0303/FP32/person-detection-0303.xml -d CPU Model: Person Detection FP32 - Device: CPU pts/openvino-1.3.0 -m models/intel/vehicle-detection-0202/FP16/vehicle-detection-0202.xml -d CPU Model: Vehicle Detection FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/face-detection-0206/FP16-INT8/face-detection-0206.xml -d CPU Model: Face Detection FP16-INT8 - Device: CPU pts/openvino-1.3.0 -m models/intel/face-detection-retail-0005/FP16/face-detection-retail-0005.xml -d CPU Model: Face Detection Retail FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/road-segmentation-adas-0001/FP16/road-segmentation-adas-0001.xml -d CPU Model: Road Segmentation ADAS FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/vehicle-detection-0202/FP16-INT8/vehicle-detection-0202.xml -d CPU Model: Vehicle Detection FP16-INT8 - Device: CPU pts/openvino-1.3.0 -m models/intel/weld-porosity-detection-0001/FP16/weld-porosity-detection-0001.xml -d CPU Model: Weld Porosity Detection FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/face-detection-retail-0005/FP16-INT8/face-detection-retail-0005.xml -d CPU Model: Face Detection Retail FP16-INT8 - Device: CPU pts/openvino-1.3.0 -m models/intel/road-segmentation-adas-0001/FP16-INT8/road-segmentation-adas-0001.xml -d CPU Model: Road Segmentation ADAS FP16-INT8 - Device: CPU pts/openvino-1.3.0 -m models/intel/machine-translation-nar-en-de-0002/FP16/machine-translation-nar-en-de-0002.xml -d CPU Model: Machine Translation EN To DE FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/weld-porosity-detection-0001/FP16-INT8/weld-porosity-detection-0001.xml -d CPU Model: Weld Porosity Detection FP16-INT8 - Device: CPU pts/openvino-1.3.0 -m models/intel/person-vehicle-bike-detection-2004/FP16/person-vehicle-bike-detection-2004.xml -d CPU Model: Person Vehicle Bike Detection FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/handwritten-english-recognition-0001/FP16/handwritten-english-recognition-0001.xml -d CPU Model: Handwritten English Recognition FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013.xml -d CPU Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU pts/openvino-1.3.0 -m models/intel/handwritten-english-recognition-0001/FP16-INT8/handwritten-english-recognition-0001.xml -d CPU Model: Handwritten English Recognition FP16-INT8 - Device: CPU pts/openvino-1.3.0 -m models/intel/age-gender-recognition-retail-0013/FP16-INT8/age-gender-recognition-retail-0013.xml -d CPU Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU pts/heffte-1.0.0 c2c fftw float 128 128 128 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 pts/heffte-1.0.0 r2c fftw float 128 128 128 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 pts/heffte-1.0.0 c2c fftw double 128 128 128 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 pts/heffte-1.0.0 r2c fftw double 128 128 128 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 pts/libxsmm-1.0.1 32 32 32 M N K: 32 pts/libxsmm-1.0.1 64 64 64 M N K: 64 pts/tensorflow-2.1.0 --device cpu --batch_size=16 --model=resnet50 Device: CPU - Batch Size: 16 - Model: ResNet-50 pts/tensorflow-2.1.0 --device cpu --batch_size=32 --model=resnet50 Device: CPU - Batch Size: 32 - Model: ResNet-50 pts/tensorflow-2.1.0 --device cpu --batch_size=64 --model=resnet50 Device: CPU - Batch Size: 64 - Model: ResNet-50 pts/coremark-1.0.1 CoreMark Size 666 - Iterations Per Second pts/laghos-1.0.0 -p 3 -m data/box01_hex.mesh -rs 2 -tf 5.0 -vis -pa Test: Triple Point Problem pts/laghos-1.0.0 -p 1 -m data/cube_922_hex.mesh -rs 2 -tf 0.6 -no-vis -pa Test: Sedov Blast Wave, ube_922_hex.mesh pts/compress-7zip-1.10.0 Test: Compression Rating pts/compress-7zip-1.10.0 Test: Decompression Rating pts/stockfish-1.4.0 Total Time pts/gromacs-1.8.0 mpi-build water-cut1.0_GMX50_bare/1536 Implementation: MPI CPU - Input: water_GMX50_bare pts/lammps-1.4.0 benchmark_20k_atoms.in Model: 20k Atoms pts/lammps-1.4.0 in.rhodo Model: Rhodopsin Protein pts/cassandra-1.2.0 WRITE Test: Writes pts/apache-iotdb-1.2.0 500 100 500 400 Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400 pts/apache-iotdb-1.2.0 500 100 800 400 Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400 pts/apache-iotdb-1.2.0 800 100 500 400 Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400 pts/apache-iotdb-1.2.0 800 100 800 400 Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400 pts/nginx-3.0.1 -c 500 Connections: 500 pts/nginx-3.0.1 -c 1000 Connections: 1000 pts/openssl-3.1.0 rsa4096 Algorithm: RSA4096 pts/npb-1.4.5 bt.C Test / Class: BT.C pts/npb-1.4.5 cg.C Test / Class: CG.C pts/npb-1.4.5 ep.D Test / Class: EP.D pts/npb-1.4.5 ft.C Test / Class: FT.C pts/npb-1.4.5 is.D Test / Class: IS.D pts/npb-1.4.5 lu.C Test / Class: LU.C pts/npb-1.4.5 mg.C Test / Class: MG.C pts/npb-1.4.5 sp.C Test / Class: SP.C pts/pgbench-1.14.0 -s 100 -c 800 -S Scaling Factor: 100 - Clients: 800 - Mode: Read Only pts/pgbench-1.14.0 -s 100 -c 1000 -S Scaling Factor: 100 - Clients: 1000 - Mode: Read Only pts/pgbench-1.14.0 -s 100 -c 800 Scaling Factor: 100 - Clients: 800 - Mode: Read Write pts/pgbench-1.14.0 -s 100 -c 1000 Scaling Factor: 100 - Clients: 1000 - Mode: Read Write pts/brl-cad-1.5.0 VGR Performance Metric pts/pgbench-1.14.0 -s 100 -c 800 -S Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency pts/pgbench-1.14.0 -s 100 -c 1000 -S Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency pts/pgbench-1.14.0 -s 100 -c 800 Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency pts/pgbench-1.14.0 -s 100 -c 1000 Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency pts/rodinia-1.3.2 OMP_LAVAMD Test: OpenMP LavaMD pts/rodinia-1.3.2 OMP_HOTSPOT3D Test: OpenMP HotSpot3D pts/rodinia-1.3.2 OMP_LEUKOCYTE Test: OpenMP Leukocyte pts/rodinia-1.3.2 OMP_CFD Test: OpenMP CFD Solver pts/rodinia-1.3.2 OMP_STREAMCLUSTER Test: OpenMP Streamcluster pts/incompact3d-2.0.2 input_129_nodes.i3d Input: input.i3d 129 Cells Per Direction pts/incompact3d-2.0.2 input_193_nodes.i3d Input: input.i3d 193 Cells Per Direction pts/openradioss-1.1.1 Bumper_Beam_AP_meshed_0000.rad Bumper_Beam_AP_meshed_0001.rad Model: Bumper Beam pts/openradioss-1.1.1 NEON1M11_0000.rad NEON1M11_0001.rad Model: Chrysler Neon 1M pts/openradioss-1.1.1 Cell_Phone_Drop_0000.rad Cell_Phone_Drop_0001.rad Model: Cell Phone Drop Test pts/openradioss-1.1.1 BIRD_WINDSHIELD_v1_0000.rad BIRD_WINDSHIELD_v1_0001.rad Model: Bird Strike on Windshield pts/openradioss-1.1.1 RUBBER_SEAL_IMPDISP_GEOM_0000.rad RUBBER_SEAL_IMPDISP_GEOM_0001.rad Model: Rubber O-Ring Seal Installation pts/openradioss-1.1.1 fsi_drop_container_0000.rad fsi_drop_container_0001.rad Model: INIVOL and Fluid Structure Interaction Drop Container pts/remhos-1.0.0 -m ./data/inline-quad.mesh -p 14 -rs 2 -rp 1 -dt 0.0005 -tf 0.6 -ho 1 -lo 2 -fct 3 Test: Sample Remap Example pts/avifenc-1.4.0 -s 0 Encoder Speed: 0 pts/avifenc-1.4.0 -s 2 Encoder Speed: 2 pts/avifenc-1.4.0 -s 6 Encoder Speed: 6 pts/avifenc-1.4.0 -s 6 -l Encoder Speed: 6, Lossless pts/build-gem5-1.0.0 Time To Compile pts/build-linux-kernel-1.15.0 defconfig Build: defconfig pts/build-linux-kernel-1.15.0 allmodconfig Build: allmodconfig pts/build-nodejs-1.3.0 Time To Compile pts/blender-3.6.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: BMW27 - Compute: CPU-Only pts/blender-3.6.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Classroom - Compute: CPU-Only pts/blender-3.6.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Fishy Cat - Compute: CPU-Only pts/blender-3.6.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Barbershop - Compute: CPU-Only pts/blender-3.6.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Pabellon Barcelona - Compute: CPU-Only