PTI

Intel Core i7-9750H testing with a CFL Ghibli_CFS (V1.13 BIOS) and NVIDIA GeForce RTX 2060 6GB on Arch rolling via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2011201-NE-PTI82226850
Jump To Table - Results

Statistics

Remove Outliers Before Calculating Averages

Graph Settings

Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
PTI-on
November 20 2020
  2 Minutes
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


PTIOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-9750H @ 4.50GHz (6 Cores / 12 Threads)CFL Ghibli_CFS (V1.13 BIOS)Intel Cannon Lake PCH16GB257GB Flash Drive FITNVIDIA GeForce RTX 2060 6GB (960/7000MHz)Realtek ALC289Realtek Device 3000 + Intel-AC 9560Arch rolling5.9.9-arch1-1 (x86_64)KDE Plasma 5.20.3X Server 1.20.9NVIDIA 455.384.6.0GCC 10.2.0 + Clang 11.0.0Target:ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionPTI BenchmarksSystem Logs- Scaling Governor: intel_pstate powersave - CPU Microcode: 0xde- SNA- itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Mitigation of Microcode + tsx_async_abort: Not affected

Waifu2x-NCNN Vulkan

Waifu2x-NCNN is an NCNN neural network implementation of the Waifu2x converter project and accelerated using the Vulkan API. NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. This test profile times how long it takes to increase the resolution of a sample image with Vulkan. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterWaifu2x-NCNN Vulkan 20200818Scale: 2x - Denoise: 3 - TAA: NoPTI-on0.55491.10981.66472.21962.7745SE +/- 0.394, N = 152.466

OpenBenchmarking.orgSeconds, Fewer Is BetterWaifu2x-NCNN Vulkan 20200818Scale: 2x - Denoise: 3 - TAA: YesPTI-on246810SE +/- 0.016, N = 37.217