NVIDIA Jetson AGX Xavier vs. TX2 Thermal + Power

Jetson AGX Xavier thermal and power consumption benchmarking for a future article on Phoronix by Michael Larabel.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 1812244-SP-JETSON56020
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Jetson AGX Xavier
December 24 2018
  2 Hours, 13 Minutes
Jetson TX2
December 24 2018
  4 Hours, 23 Minutes
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Jetson AGX Xavier

Processor: ARMv8 rev 0 @ 2.27GHz (8 Cores), Motherboard: jetson-xavier, Memory: 16384MB, Disk: 31GB HBG4a2, Graphics: NVIDIA Tegra Xavier, Monitor: ASUS VP28U

OS: Ubuntu 18.04, Kernel: 4.9.108-tegra (aarch64), Desktop: Unity 7.5.0, Display Server: X Server 1.19.6, Display Driver: NVIDIA 31.0.2, OpenGL: 4.6.0, Vulkan: 1.1.76, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Disk Mount Options Notes: data=ordered,relatime,rw
Python Notes: Python 2.7.15rc1 + Python 3.6.5

Jetson TX2

Processor: ARMv8 rev 3 @ 2.04GHz (4 Cores / 6 Threads), Motherboard: quill, Memory: 8192MB, Disk: 31GB 032G34, Graphics: NVIDIA Tegra X2, Monitor: ASUS VP28U

OS: Ubuntu 16.04, Kernel: 4.4.38-tegra (aarch64), Desktop: Unity 7.4.0, Display Server: X Server 1.18.4, Display Driver: NVIDIA 28.2.1, OpenGL: 4.5.0, Compiler: GCC 5.4.0 20160609 + CUDA 9.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Disk Mount Options Notes: data=ordered,relatime,rw
Python Notes: Python 2.7.12 + Python 3.5.2

NVIDIA Jetson AGX Xavier vs. TX2 Thermal + PowerProcessorMotherboardMemoryDiskGraphicsMonitorOSKernelDesktopDisplay ServerDisplay DriverOpenGLVulkanCompilerFile-SystemScreen ResolutionJetson AGX XavierJetson TX2ARMv8 rev 0 @ 2.27GHz (8 Cores)jetson-xavier16384MB31GB HBG4a2NVIDIA Tegra XavierASUS VP28UUbuntu 18.044.9.108-tegra (aarch64)Unity 7.5.0X Server 1.19.6NVIDIA 31.0.24.6.01.1.76GCC 7.3.0 + CUDA 10.0ext43840x2160ARMv8 rev 3 @ 2.04GHz (4 Cores / 6 Threads)quill8192MB31GB 032G34NVIDIA Tegra X2Ubuntu 16.044.4.38-tegra (aarch64)Unity 7.4.0X Server 1.18.4NVIDIA 28.2.14.5.0GCC 5.4.0 20160609 + CUDA 9.0OpenBenchmarking.orgCompiler Details- Jetson AGX Xavier: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v - Jetson TX2: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v Processor Details- Scaling Governor: tegra_cpufreq schedutilDisk Mount Options Details- data=ordered,relatime,rwPython Details- Jetson AGX Xavier: Python 2.7.15rc1 + Python 3.6.5- Jetson TX2: Python 2.7.12 + Python 3.5.2

Jetson AGX Xavier vs. Jetson TX2 ComparisonPhoronix Test SuiteBaseline+544.2%+544.2%+1088.4%+1088.4%+1632.6%+1632.6%29.3%AlexNet - INT8 - 32 - Disabled874.2%VGG16 - FP16 - 32 - Disabled572.7%R.4.b.P351.2%AlexNet - FP16 - 32 - Disabled323.3%Total Time - 4.1.R.P.P290.5%GoogleNet - FP16 - 32 - Disabled288.6%P.N.T.T.2.0.0230.4%VGG16 - INT8 - 32 - Disabled2176.7%1.H.M.2.D179.8%WAV To MP3170.6%T.T.C.S.P.M128.2%C.u.1.0.3.s.i.i.C.L.9116.3%GoogleNet - INT8 - 32 - Disabled1132.6%Time To Compile96.7%A.C.P79.9%T.F.A.T.T65.7%T.S.I55.3%T.T.C.C.G.C42.6%P.B.S41.4%WAV To FLAC18.4%P.P.S13.1%NVIDIA TensorRT InferenceNVIDIA TensorRT InferenceOpenSSLNVIDIA TensorRT InferenceC-RayNVIDIA TensorRT InferenceRust Prime BenchmarkNVIDIA TensorRT InferenceasmFishLAME MP3 EncodingRust MandelbrotXZ CompressionNVIDIA TensorRT InferenceTimed Linux Kernel CompilationTSCPPyBenchSQLiteGitPHPBenchScikit-LearnFLAC Audio EncodingHimeno BenchmarkJetson AGX XavierJetson TX2

NVIDIA Jetson AGX Xavier vs. TX2 Thermal + Powertensorrt-inference: AlexNet - INT8 - 32 - Disabledtensorrt-inference: GoogleNet - INT8 - 32 - Disabledtensorrt-inference: AlexNet - FP16 - 32 - Disabledtensorrt-inference: GoogleNet - FP16 - 32 - Disabledtensorrt-inference: VGG16 - INT8 - 32 - Disabledtensorrt-inference: VGG16 - FP16 - 32 - Disabledhimeno: Poisson Pressure Solvertscp: AI Chess Performanceasmfish: 1024 Hash Memory, 26 Depthphpbench: PHP Benchmark Suiteopenssl: RSA 4096-bit Performancepybench: Total For Average Test Timesc-ray: Total Time - 4K, 16 Rays Per Pixelencode-mp3: WAV To MP3encode-flac: WAV To FLACbuild-linux-kernel: Time To Compilesqlite: Timed SQLite Insertionscompress-xz: Compressing ubuntu-16.04.3-server-i386.img, Compression Level 9git: Time To Complete Common Git Commandsscikit-learn: darktable: Boat - CPU-onlyrust-prime: Prime Number Test To 200,000,000rust-mandel: Time To Complete Serial/Parallel MandelbrotJetson AGX XavierJetson TX22981162719818904462472776602678193464189005573323716835.4755.1678978.6514712.5322528.1732.5011030613246822919.5936.722453670882928565133638127536565695.9865.331552122.1431817.87174107.39251OpenBenchmarking.org

System Temperature Monitor

OpenBenchmarking.orgCelsiusSystem Temperature MonitorPhoronix Test Suite System MonitoringJetson AGX XavierJetson TX21224364860Min: 34 / Avg: 42.47 / Max: 50.5Min: 42 / Avg: 50.5 / Max: 61

System Power Consumption Monitor

OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System MonitoringJetson AGX XavierJetson TX21020304050Min: 11.5 / Avg: 20.65 / Max: 47.1Min: 5.1 / Avg: 8.99 / Max: 17.5

NVIDIA TensorRT Inference

This test profile uses any existing system installation of NVIDIA TensorRT for carrying out inference benchmarks with various neural networks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX26001200180024003000SE +/- 145.87, N = 3SE +/- 1.25, N = 32981306
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX25001000150020002500Min: 2688.99 / Avg: 2980.71 / Max: 3129.92Min: 304.21 / Avg: 306.44 / Max: 308.52

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX230060090012001500SE +/- 25.05, N = 3SE +/- 1.01, N = 31627132
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX230060090012001500Min: 1581.65 / Avg: 1626.99 / Max: 1668.13Min: 129.93 / Avg: 131.95 / Max: 133.01

OpenBenchmarking.orgImages Per Second Per Watt, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX24080120160200193.7133.98

OpenBenchmarking.orgImages Per Second Per Watt, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX2306090120150113.8853.46

OpenBenchmarking.orgImages Per Second Per Watt, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX220406080100105.8513.66

OpenBenchmarking.orgImages Per Second Per Watt, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX2122436486053.0223.97

OpenBenchmarking.orgImages Per Second Per Watt, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX251015202518.551.42

OpenBenchmarking.orgImages Per Second Per Watt, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX236912159.602.99

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX2400800120016002000SE +/- 23.68, N = 3SE +/- 12.79, N = 31981468
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: AlexNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX230060090012001500Min: 1943.63 / Avg: 1980.72 / Max: 2024.77Min: 448.67 / Avg: 467.96 / Max: 492.17

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX22004006008001000SE +/- 17.85, N = 3SE +/- 7.62, N = 3890229
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: GoogleNet - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX2160320480640800Min: 863.52 / Avg: 890.11 / Max: 924.04Min: 213.77 / Avg: 229 / Max: 236.86

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX2100200300400500SE +/- 11.20, N = 3SE +/- 0.03, N = 3446.0019.59
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: INT8 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX280160240320400Min: 434.17 / Avg: 446.33 / Max: 468.71Min: 19.55 / Avg: 19.59 / Max: 19.65

OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX250100150200250SE +/- 0.65, N = 3SE +/- 0.13, N = 3247.0036.72
OpenBenchmarking.orgImages Per Second, More Is BetterNVIDIA TensorRT InferenceNeural Network: VGG16 - Precision: FP16 - Batch Size: 32 - DLA Cores: DisabledJetson AGX XavierJetson TX24080120160200Min: 245.84 / Avg: 246.64 / Max: 247.94Min: 36.58 / Avg: 36.72 / Max: 36.98

Himeno Benchmark

OpenBenchmarking.orgMFLOPS Per Watt, More Is BetterHimeno Benchmark 3.0Poisson Pressure SolverJetson AGX XavierJetson TX281624324019.0534.98

OpenBenchmarking.orgMFLOPS, More Is BetterHimeno Benchmark 3.0Poisson Pressure SolverJetson AGX XavierJetson TX260120180240300SE +/- 0.18, N = 3SE +/- 1.76, N = 32772451. (CC) gcc options: -O3
OpenBenchmarking.orgMFLOPS, More Is BetterHimeno Benchmark 3.0Poisson Pressure SolverJetson AGX XavierJetson TX250100150200250Min: 277.1 / Avg: 277.41 / Max: 277.74Min: 242.19 / Avg: 245.23 / Max: 248.291. (CC) gcc options: -O3

TSCP

OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterTSCP 1.81AI Chess PerformanceJetson AGX XavierJetson TX213K26K39K52K65K48371.2160776.16

OpenBenchmarking.orgNodes Per Second, More Is BetterTSCP 1.81AI Chess PerformanceJetson AGX XavierJetson TX2140K280K420K560K700KSE +/- 1845.75, N = 5SE +/- 213.20, N = 56602673670881. (CC) gcc options: -O3 -march=native
OpenBenchmarking.orgNodes Per Second, More Is BetterTSCP 1.81AI Chess PerformanceJetson AGX XavierJetson TX2110K220K330K440K550KMin: 654908 / Avg: 660267 / Max: 665190Min: 366452 / Avg: 367087.6 / Max: 3674301. (CC) gcc options: -O3 -march=native

asmFish

This is a test of asmFish, an advanced chess benchmark written in Assembly. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes/second, More Is BetterasmFish 2018-07-231024 Hash Memory, 26 DepthJetson AGX XavierJetson TX22M4M6M8M10MSE +/- 59696.43, N = 3SE +/- 47318.56, N = 381934642928565
OpenBenchmarking.orgNodes/second, More Is BetterasmFish 2018-07-231024 Hash Memory, 26 DepthJetson AGX XavierJetson TX21.4M2.8M4.2M5.6M7MMin: 8130176 / Avg: 8193463.67 / Max: 8312783Min: 2848889 / Avg: 2928565 / Max: 3012629

OpenBenchmarking.orgNodes/second Per Watt, More Is BetterasmFish 2018-07-231024 Hash Memory, 26 DepthJetson AGX XavierJetson TX270K140K210K280K350K322296.99322497.70

Meta Performance Per Watt

OpenBenchmarking.orgPerformance Per Watt, More Is BetterMeta Performance Per WattPerformance Per WattJetson AGX XavierJetson TX2200K400K600K800K1000K822887.13311895.90

PHPBench

PHPBench is a benchmark suite for PHP. It performs a large number of simple tests in order to bench various aspects of the PHP interpreter. PHPBench can be used to compare hardware, operating systems, PHP versions, PHP accelerators and caches, compiler options, etc. The number of iterations used is 1,000,000. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterPHPBench 0.8.1PHP Benchmark SuiteJetson AGX XavierJetson TX240K80K120K160K200KSE +/- 2893.66, N = 3SE +/- 1322.96, N = 3189005133638
OpenBenchmarking.orgScore, More Is BetterPHPBench 0.8.1PHP Benchmark SuiteJetson AGX XavierJetson TX230K60K90K120K150KMin: 183734 / Avg: 189004.67 / Max: 193710Min: 131042 / Avg: 133638.33 / Max: 135378

OpenBenchmarking.orgScore Per Watt, More Is BetterPHPBench 0.8.1PHP Benchmark SuiteJetson AGX XavierJetson TX24K8K12K16K20K12317.1819097.64

OpenSSL

OpenBenchmarking.orgSigns Per Second Per Watt, More Is BetterOpenSSL 1.1.1RSA 4096-bit PerformanceJetson AGX XavierJetson TX261218243026.1716.38

OpenBenchmarking.orgSigns Per Second, More Is BetterOpenSSL 1.1.1RSA 4096-bit PerformanceJetson AGX XavierJetson TX2120240360480600SE +/- 5.74, N = 3SE +/- 0.36, N = 35731271. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgSigns Per Second, More Is BetterOpenSSL 1.1.1RSA 4096-bit PerformanceJetson AGX XavierJetson TX2100200300400500Min: 564.4 / Avg: 573.47 / Max: 584.1Min: 126.3 / Avg: 127 / Max: 127.51. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

NVIDIA TensorRT Inference

MinAvgMaxJetson AGX Xavier36.037.739.0Jetson TX243.045.749.0OpenBenchmarking.orgCelsius, Fewer Is BetterNVIDIA TensorRT InferenceSystem Temperature Monitor1428425670

MinAvgMaxJetson AGX Xavier38.039.841.0Jetson TX247.047.649.0OpenBenchmarking.orgCelsius, Fewer Is BetterNVIDIA TensorRT InferenceSystem Temperature Monitor1428425670

MinAvgMaxJetson AGX Xavier39.041.543.5Jetson TX246.548.752.0OpenBenchmarking.orgCelsius, Fewer Is BetterNVIDIA TensorRT InferenceSystem Temperature Monitor1530456075

MinAvgMaxJetson AGX Xavier42.544.546.5Jetson TX248.550.252.5OpenBenchmarking.orgCelsius, Fewer Is BetterNVIDIA TensorRT InferenceSystem Temperature Monitor1530456075

MinAvgMaxJetson AGX Xavier44.547.350.5Jetson TX249.556.261.0OpenBenchmarking.orgCelsius, Fewer Is BetterNVIDIA TensorRT InferenceSystem Temperature Monitor20406080100

MinAvgMaxJetson AGX Xavier42.545.448.0Jetson TX252.556.560.0OpenBenchmarking.orgCelsius, Fewer Is BetterNVIDIA TensorRT InferenceSystem Temperature Monitor1632486480

C-Ray

MinAvgMaxJetson AGX Xavier46.548.649.0Jetson TX252.053.959.0OpenBenchmarking.orgCelsius, Fewer Is BetterC-Ray 1.1System Temperature Monitor1632486480

LAME MP3 Encoding

MinAvgMaxJetson AGX Xavier40.541.242.0Jetson TX248.049.451.0OpenBenchmarking.orgCelsius, Fewer Is BetterLAME MP3 Encoding 3.100System Temperature Monitor1530456075

FLAC Audio Encoding

MinAvgMaxJetson AGX Xavier36.538.740.5Jetson TX246.047.348.0OpenBenchmarking.orgCelsius, Fewer Is BetterFLAC Audio Encoding 1.3.2System Temperature Monitor1428425670

PHPBench

MinAvgMaxJetson AGX Xavier36.537.238.0Jetson TX245.546.547.0OpenBenchmarking.orgCelsius, Fewer Is BetterPHPBench 0.8.1System Temperature Monitor1428425670

PyBench

MinAvgMaxJetson AGX Xavier35.536.537.5Jetson TX244.545.746.5OpenBenchmarking.orgCelsius, Fewer Is BetterPyBench 2018-02-16System Temperature Monitor1428425670

Timed Linux Kernel Compilation

MinAvgMaxJetson AGX Xavier35.545.147.0Jetson TX243.550.752.0OpenBenchmarking.orgCelsius, Fewer Is BetterTimed Linux Kernel Compilation 4.18System Temperature Monitor1530456075

SQLite

MinAvgMaxJetson AGX Xavier35.536.938.5Jetson TX242.044.347.0OpenBenchmarking.orgCelsius, Fewer Is BetterSQLite 3.22System Temperature Monitor1428425670

asmFish

MinAvgMaxJetson AGX Xavier34.545.947.5Jetson TX245.050.352.0OpenBenchmarking.orgCelsius, Fewer Is BetterasmFish 2018-07-23System Temperature Monitor1530456075

XZ Compression

MinAvgMaxJetson AGX Xavier39.541.644.0Jetson TX248.050.150.5OpenBenchmarking.orgCelsius, Fewer Is BetterXZ Compression 5.2.4System Temperature Monitor1428425670

Git

MinAvgMaxJetson AGX Xavier37.038.139.0Jetson TX248.048.249.0OpenBenchmarking.orgCelsius, Fewer Is BetterGitSystem Temperature Monitor1428425670

Himeno Benchmark

MinAvgMaxJetson AGX Xavier35.536.437.0Jetson TX246.547.448.0OpenBenchmarking.orgCelsius, Fewer Is BetterHimeno Benchmark 3.0System Temperature Monitor1428425670

OpenSSL

MinAvgMaxJetson AGX Xavier34.540.041.5Jetson TX247.048.048.5OpenBenchmarking.orgCelsius, Fewer Is BetterOpenSSL 1.1.1System Temperature Monitor1428425670

Scikit-Learn

MinAvgMaxJetson AGX Xavier35.036.637.5Jetson TX245.546.347.0OpenBenchmarking.orgCelsius, Fewer Is BetterScikit-Learn 0.17.1System Temperature Monitor1428425670

Darktable

MinAvgMaxJetson AGX Xavier35.541.944.5OpenBenchmarking.orgCelsius, Fewer Is BetterDarktableSystem Temperature Monitor1224364860

TSCP

MinAvgMaxJetson AGX Xavier37.037.337.5Jetson TX244.044.344.5OpenBenchmarking.orgCelsius, Fewer Is BetterTSCP 1.81System Temperature Monitor1224364860

Rust Prime Benchmark

MinAvgMaxJetson AGX Xavier37.538.539.0Jetson TX243.545.746.0OpenBenchmarking.orgCelsius, Fewer Is BetterRust Prime BenchmarkSystem Temperature Monitor1224364860

Rust Mandelbrot

MinAvgMaxJetson AGX Xavier35.537.540.0Jetson TX244.546.347.5OpenBenchmarking.orgCelsius, Fewer Is BetterRust MandelbrotSystem Temperature Monitor1428425670

PyBench

This test profile reports the total time of the different average timed test results from PyBench. PyBench reports average test times for different functions such as BuiltinFunctionCalls and NestedForLoops, with this total result providing a rough estimate as to Python's average performance on a given system. This test profile runs PyBench each time for 20 rounds. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test TimesJetson AGX XavierJetson TX212002400360048006000SE +/- 8.74, N = 3SE +/- 2.91, N = 332375365
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test TimesJetson AGX XavierJetson TX29001800270036004500Min: 3220 / Avg: 3237.33 / Max: 3248Min: 5360 / Avg: 5364.67 / Max: 5370

C-Ray

This is a test of C-Ray, a simple raytracer designed to test the floating-point CPU performance. This test is multi-threaded (16 threads per core), will shoot 8 rays per pixel for anti-aliasing, and will generate a 1600 x 1200 image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterC-Ray 1.1Total Time - 4K, 16 Rays Per PixelJetson AGX XavierJetson TX2140280420560700SE +/- 0.94, N = 3SE +/- 43.48, N = 31686561. (CC) gcc options: -lm -lpthread -O3
OpenBenchmarking.orgSeconds, Fewer Is BetterC-Ray 1.1Total Time - 4K, 16 Rays Per PixelJetson AGX XavierJetson TX2120240360480600Min: 166.91 / Avg: 168.21 / Max: 170.03Min: 568.75 / Avg: 655.65 / Max: 701.951. (CC) gcc options: -lm -lpthread -O3

LAME MP3 Encoding

LAME is an MP3 encoder licensed under the LGPL. This test measures the time required to encode a WAV file to MP3 format. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterLAME MP3 Encoding 3.100WAV To MP3Jetson AGX XavierJetson TX220406080100SE +/- 0.26, N = 3SE +/- 0.14, N = 335.4795.981. (CC) gcc options: -lm
OpenBenchmarking.orgSeconds, Fewer Is BetterLAME MP3 Encoding 3.100WAV To MP3Jetson AGX XavierJetson TX220406080100Min: 35.01 / Avg: 35.47 / Max: 35.89Min: 95.83 / Avg: 95.98 / Max: 96.271. (CC) gcc options: -lm

FLAC Audio Encoding

This test times how long it takes to encode a sample WAV file to FLAC format five times. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterFLAC Audio Encoding 1.3.2WAV To FLACJetson AGX XavierJetson TX21530456075SE +/- 0.34, N = 5SE +/- 0.16, N = 555.1665.331. (CXX) g++ options: -O2 -fvisibility=hidden -logg -lm
OpenBenchmarking.orgSeconds, Fewer Is BetterFLAC Audio Encoding 1.3.2WAV To FLACJetson AGX XavierJetson TX21326395265Min: 54.44 / Avg: 55.16 / Max: 56.45Min: 64.88 / Avg: 65.33 / Max: 65.751. (CXX) g++ options: -O2 -fvisibility=hidden -logg -lm

Timed Linux Kernel Compilation

This test times how long it takes to build the Linux kernel in a default configuration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 4.18Time To CompileJetson AGX XavierJetson TX230060090012001500SE +/- 5.38, N = 3SE +/- 3.04, N = 37891552
OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 4.18Time To CompileJetson AGX XavierJetson TX230060090012001500Min: 781.03 / Avg: 788.6 / Max: 799.01Min: 1548.83 / Avg: 1552.06 / Max: 1558.13

SQLite

This is a simple benchmark of SQLite. At present this test profile just measures the time to perform a pre-defined number of insertions on an indexed database. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSQLite 3.22Timed SQLite InsertionsJetson AGX XavierJetson TX2306090120150SE +/- 0.97, N = 3SE +/- 0.01, N = 378.65122.141. (CC) gcc options: -O2 -lz -ldl -lpthread
OpenBenchmarking.orgSeconds, Fewer Is BetterSQLite 3.22Timed SQLite InsertionsJetson AGX XavierJetson TX220406080100Min: 77.51 / Avg: 78.65 / Max: 80.57Min: 122.13 / Avg: 122.14 / Max: 122.151. (CC) gcc options: -O2 -lz -ldl -lpthread

XZ Compression

This test measures the time needed to compress a sample file (an Ubuntu file-system image) using XZ compression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterXZ Compression 5.2.4Compressing ubuntu-16.04.3-server-i386.img, Compression Level 9Jetson AGX XavierJetson TX270140210280350SE +/- 0.55, N = 3SE +/- 1.96, N = 31473181. (CC) gcc options: -pthread -fvisibility=hidden -O2
OpenBenchmarking.orgSeconds, Fewer Is BetterXZ Compression 5.2.4Compressing ubuntu-16.04.3-server-i386.img, Compression Level 9Jetson AGX XavierJetson TX260120180240300Min: 146.26 / Avg: 147.03 / Max: 148.09Min: 313.68 / Avg: 317.51 / Max: 320.161. (CC) gcc options: -pthread -fvisibility=hidden -O2

Git

This test measures the time needed to carry out some sample Git operations on an example, static repository that happens to be a copy of the GNOME GTK tool-kit repository. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterGitTime To Complete Common Git CommandsJetson AGX XavierJetson TX248121620SE +/- 0.17, N = 3SE +/- 0.10, N = 312.5317.871. Jetson AGX Xavier: git version 2.17.12. Jetson TX2: git version 2.7.4
OpenBenchmarking.orgSeconds, Fewer Is BetterGitTime To Complete Common Git CommandsJetson AGX XavierJetson TX2510152025Min: 12.36 / Avg: 12.53 / Max: 12.87Min: 17.73 / Avg: 17.87 / Max: 18.051. Jetson AGX Xavier: git version 2.17.12. Jetson TX2: git version 2.7.4

Scikit-Learn

Scikit-learn is a Python module for machine learning Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 0.17.1Jetson AGX XavierJetson TX250100150200250SE +/- 0.11, N = 3SE +/- 0.70, N = 3225174
OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 0.17.1Jetson AGX XavierJetson TX24080120160200Min: 224.99 / Avg: 225.21 / Max: 225.36Min: 173.22 / Avg: 174.36 / Max: 175.65

Darktable

Darktable is an open-source photography / workflow application this will use any system-installed Darktable program or on Windows will automatically download the pre-built binary from the project. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.4.2Test: Boat - Acceleration: CPU-onlyJetson AGX Xavier714212835SE +/- 2.12, N = 328.17

Rust Prime Benchmark

Based on petehunt/rust-benchmark, this is a prime number benchmark that is multi-threaded and written in Rustlang. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRust Prime BenchmarkPrime Number Test To 200,000,000Jetson AGX XavierJetson TX220406080100SE +/- 0.07, N = 3SE +/- 0.11, N = 332.50107.391. (CC) gcc options: -pie -nodefaultlibs -ldl -lrt -lpthread -lgcc_s -lc -lm -lutil
OpenBenchmarking.orgSeconds, Fewer Is BetterRust Prime BenchmarkPrime Number Test To 200,000,000Jetson AGX XavierJetson TX220406080100Min: 32.35 / Avg: 32.5 / Max: 32.6Min: 107.19 / Avg: 107.39 / Max: 107.561. (CC) gcc options: -pie -nodefaultlibs -ldl -lrt -lpthread -lgcc_s -lc -lm -lutil

Rust Mandelbrot

This test profile is of the combined time for the serial and parallel Mandelbrot sets written in Rustlang via willi-kappler/mandel-rust. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRust MandelbrotTime To Complete Serial/Parallel MandelbrotJetson AGX XavierJetson TX250100150200250SE +/- 2.50, N = 3SE +/- 0.83, N = 31102511. (CC) gcc options: -pie -nodefaultlibs -lutil -ldl -lrt -lpthread -lgcc_s -lc -lm
OpenBenchmarking.orgSeconds, Fewer Is BetterRust MandelbrotTime To Complete Serial/Parallel MandelbrotJetson AGX XavierJetson TX250100150200250Min: 107.22 / Avg: 109.8 / Max: 114.79Min: 249.35 / Avg: 251.01 / Max: 251.881. (CC) gcc options: -pie -nodefaultlibs -lutil -ldl -lrt -lpthread -lgcc_s -lc -lm

NVIDIA TensorRT Inference

MinAvgMaxJetson AGX Xavier11.615.419.8Jetson TX25.79.016.4OpenBenchmarking.orgWatts, Fewer Is BetterNVIDIA TensorRT InferenceSystem Power Consumption Monitor612182430

MinAvgMaxJetson AGX Xavier12.217.426.5Jetson TX25.98.815.1OpenBenchmarking.orgWatts, Fewer Is BetterNVIDIA TensorRT InferenceSystem Power Consumption Monitor816243240

MinAvgMaxJetson AGX Xavier11.815.438.9Jetson TX25.39.716.0OpenBenchmarking.orgWatts, Fewer Is BetterNVIDIA TensorRT InferenceSystem Power Consumption Monitor1122334455

MinAvgMaxJetson AGX Xavier12.016.842.7Jetson TX26.09.615.4OpenBenchmarking.orgWatts, Fewer Is BetterNVIDIA TensorRT InferenceSystem Power Consumption Monitor1224364860

MinAvgMaxJetson AGX Xavier12.624.143.9Jetson TX25.613.817.5OpenBenchmarking.orgWatts, Fewer Is BetterNVIDIA TensorRT InferenceSystem Power Consumption Monitor1224364860

MinAvgMaxJetson AGX Xavier11.925.747.1Jetson TX25.812.316.4OpenBenchmarking.orgWatts, Fewer Is BetterNVIDIA TensorRT InferenceSystem Power Consumption Monitor1428425670

C-Ray

MinAvgMaxJetson AGX Xavier11.825.926.4Jetson TX26.59.19.4OpenBenchmarking.orgWatts, Fewer Is BetterC-Ray 1.1System Power Consumption Monitor816243240

LAME MP3 Encoding

MinAvgMaxJetson AGX Xavier12.815.315.7Jetson TX25.77.07.1OpenBenchmarking.orgWatts, Fewer Is BetterLAME MP3 Encoding 3.100System Power Consumption Monitor510152025

FLAC Audio Encoding

MinAvgMaxJetson AGX Xavier12.215.415.7Jetson TX25.47.17.2OpenBenchmarking.orgWatts, Fewer Is BetterFLAC Audio Encoding 1.3.2System Power Consumption Monitor510152025

PHPBench

MinAvgMaxJetson AGX Xavier11.715.315.7Jetson TX25.37.07.2OpenBenchmarking.orgWatts, Fewer Is BetterPHPBench 0.8.1System Power Consumption Monitor510152025

PyBench

MinAvgMaxJetson AGX Xavier12.815.515.7Jetson TX25.57.07.2OpenBenchmarking.orgWatts, Fewer Is BetterPyBench 2018-02-16System Power Consumption Monitor510152025

Timed Linux Kernel Compilation

MinAvgMaxJetson AGX Xavier12.023.925.0Jetson TX25.58.99.3OpenBenchmarking.orgWatts, Fewer Is BetterTimed Linux Kernel Compilation 4.18System Power Consumption Monitor816243240

SQLite

MinAvgMaxJetson AGX Xavier12.013.013.4Jetson TX25.25.35.4OpenBenchmarking.orgWatts, Fewer Is BetterSQLite 3.22System Power Consumption Monitor48121620

asmFish

MinAvgMaxJetson AGX Xavier11.625.425.8Jetson TX28.19.19.3OpenBenchmarking.orgWatts, Fewer Is BetterasmFish 2018-07-23System Power Consumption Monitor816243240

XZ Compression

MinAvgMaxJetson AGX Xavier12.419.021.7Jetson TX25.78.78.9OpenBenchmarking.orgWatts, Fewer Is BetterXZ Compression 5.2.4System Power Consumption Monitor612182430

Git

MinAvgMaxJetson AGX Xavier11.514.615.6Jetson TX25.66.77.2OpenBenchmarking.orgWatts, Fewer Is BetterGitSystem Power Consumption Monitor510152025

Himeno Benchmark

MinAvgMaxJetson AGX Xavier12.414.614.9Jetson TX25.57.07.2OpenBenchmarking.orgWatts, Fewer Is BetterHimeno Benchmark 3.0System Power Consumption Monitor510152025

OpenSSL

MinAvgMaxJetson AGX Xavier12.421.924.0Jetson TX25.47.88.3OpenBenchmarking.orgWatts, Fewer Is BetterOpenSSL 1.1.1System Power Consumption Monitor816243240

Scikit-Learn

MinAvgMaxJetson AGX Xavier11.816.016.3Jetson TX25.67.17.2OpenBenchmarking.orgWatts, Fewer Is BetterScikit-Learn 0.17.1System Power Consumption Monitor510152025

Darktable

MinAvgMaxJetson AGX Xavier11.824.630.7OpenBenchmarking.orgWatts, Fewer Is BetterDarktableSystem Power Consumption Monitor918273645

TSCP

MinAvgMaxJetson AGX Xavier12.413.714.3Jetson TX25.26.06.4OpenBenchmarking.orgWatts, Fewer Is BetterTSCP 1.81System Power Consumption Monitor510152025

Rust Prime Benchmark

MinAvgMaxJetson AGX Xavier12.818.619.4Jetson TX25.37.57.7OpenBenchmarking.orgWatts, Fewer Is BetterRust Prime BenchmarkSystem Power Consumption Monitor612182430

Rust Mandelbrot

MinAvgMaxJetson AGX Xavier13.317.321.8Jetson TX25.67.58.3OpenBenchmarking.orgWatts, Fewer Is BetterRust MandelbrotSystem Power Consumption Monitor612182430

83 Results Shown

System Temperature Monitor:
  Phoronix Test Suite System Monitoring:
    Celsius
    Watts
NVIDIA TensorRT Inference:
  AlexNet - INT8 - 32 - Disabled
  GoogleNet - INT8 - 32 - Disabled
NVIDIA TensorRT Inference:
  AlexNet - INT8 - 32 - Disabled
  AlexNet - FP16 - 32 - Disabled
  GoogleNet - INT8 - 32 - Disabled
  GoogleNet - FP16 - 32 - Disabled
  VGG16 - INT8 - 32 - Disabled
  VGG16 - FP16 - 32 - Disabled
NVIDIA TensorRT Inference:
  AlexNet - FP16 - 32 - Disabled
  GoogleNet - FP16 - 32 - Disabled
  VGG16 - INT8 - 32 - Disabled
  VGG16 - FP16 - 32 - Disabled
Himeno Benchmark
Himeno Benchmark
TSCP
TSCP
asmFish
asmFish:
  1024 Hash Memory, 26 Depth
  Performance Per Watt
PHPBench
PHPBench:
  PHP Benchmark Suite
  RSA 4096-bit Performance
OpenSSL
NVIDIA TensorRT Inference:
  System Temp Monitor:
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
    Celsius
PyBench
C-Ray
LAME MP3 Encoding
FLAC Audio Encoding
Timed Linux Kernel Compilation
SQLite
XZ Compression
Git
Scikit-Learn
Darktable
Rust Prime Benchmark
Rust Mandelbrot
NVIDIA TensorRT Inference:
  System Power Consumption Monitor:
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts

Jetson AGX Xavier

Processor: ARMv8 rev 0 @ 2.27GHz (8 Cores), Motherboard: jetson-xavier, Memory: 16384MB, Disk: 31GB HBG4a2, Graphics: NVIDIA Tegra Xavier, Monitor: ASUS VP28U

OS: Ubuntu 18.04, Kernel: 4.9.108-tegra (aarch64), Desktop: Unity 7.5.0, Display Server: X Server 1.19.6, Display Driver: NVIDIA 31.0.2, OpenGL: 4.6.0, Vulkan: 1.1.76, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Disk Mount Options Notes: data=ordered,relatime,rw
Python Notes: Python 2.7.15rc1 + Python 3.6.5

Testing initiated at 24 December 2018 09:23 by user NVIDIA.

Jetson TX2

Processor: ARMv8 rev 3 @ 2.04GHz (4 Cores / 6 Threads), Motherboard: quill, Memory: 8192MB, Disk: 31GB 032G34, Graphics: NVIDIA Tegra X2, Monitor: ASUS VP28U

OS: Ubuntu 16.04, Kernel: 4.4.38-tegra (aarch64), Desktop: Unity 7.4.0, Display Server: X Server 1.18.4, Display Driver: NVIDIA 28.2.1, OpenGL: 4.5.0, Compiler: GCC 5.4.0 20160609 + CUDA 9.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=aarch64-linux-gnu --disable-browser-plugin --disable-libquadmath --disable-werror --enable-checking=release --enable-clocale=gnu --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --target=aarch64-linux-gnu --with-arch-directory=aarch64 --with-default-libstdcxx-abi=new -v
Processor Notes: Scaling Governor: tegra_cpufreq schedutil
Disk Mount Options Notes: data=ordered,relatime,rw
Python Notes: Python 2.7.12 + Python 3.5.2

Testing initiated at 24 December 2018 20:59 by user NVIDIA.