fs

Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.04 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 2311191-PTS-FS16700400
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November 18 2023
  2 Hours, 15 Minutes
b
November 18 2023
  2 Hours, 16 Minutes
c
November 18 2023
  2 Hours, 15 Minutes
d
November 18 2023
  7 Hours, 13 Minutes
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  3 Hours, 30 Minutes

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s

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9
Python Notes: Python 3.10.12
Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

b

c

d

Processor: Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads), Motherboard: Dell 0DXP1F (3.7.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Micron 2300 NVMe 512GB, Graphics: Intel Xe TGL GT2 15GB (1350MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

OS: Ubuntu 22.04, Kernel: 6.2.0-36-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 1920x1200

fsOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads)Dell 0DXP1F (3.7.0 BIOS)Intel Tiger Lake-LP16GBMicron 2300 NVMe 512GBIntel Xe TGL GT2 15GB (1350MHz)Realtek ALC289Intel Wi-Fi 6 AX201Ubuntu 22.046.2.0-36-generic (x86_64)GNOME Shell 42.2X Server + Wayland4.6 Mesa 22.0.1OpenCL 3.01.3.204GCC 11.4.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLVulkanCompilerFile-SystemScreen ResolutionFs PerformanceSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9 - Python 3.10.12- gather_data_sampling: Mitigation of Microcode + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

sbcdResult OverviewPhoronix Test Suite100%106%113%119%PyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchBlenderPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchBlenderBlenderPyTorchBlenderCPU - 1 - ResNet-50CPU - 1 - ResNet-152CPU - 16 - ResNet-50CPU - 16 - ResNet-152CPU - 32 - ResNet-50CPU - 256 - ResNet-50CPU - 64 - ResNet-152CPU - 256 - ResNet-152Classroom - CPU-OnlyCPU - 16 - Efficientnet_v2_lCPU - 256 - Efficientnet_v2_lCPU - 512 - ResNet-152CPU - 32 - ResNet-152CPU - 1 - Efficientnet_v2_lCPU - 512 - ResNet-50CPU - 64 - ResNet-50CPU - 64 - Efficientnet_v2_lCPU - 512 - Efficientnet_v2_lBMW27 - CPU-OnlyPabellon Barcelona - CPU-OnlyCPU - 32 - Efficientnet_v2_lFishy Cat - CPU-Only

fspytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lblender: BMW27 - CPU-Onlyblender: Classroom - CPU-Onlyblender: Fishy Cat - CPU-Onlyblender: Pabellon Barcelona - CPU-Onlysbcd31.0811.5114.2313.8613.825.4913.905.5713.835.545.555.567.374.084.114.104.134.10417.281100.02528.211401.8830.159.9313.7813.6513.755.6313.765.5813.745.615.605.597.324.114.124.114.084.12417.641103.33528.721405.3730.6210.9713.7813.7913.795.6213.815.6113.815.615.595.597.364.134.124.124.124.12416.741101.16528.011401.1324.759.7913.8113.5313.795.5813.685.6213.775.625.625.627.334.134.114.124.124.11416.311113.84528.781402.14OpenBenchmarking.org

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50sbcd714212835SE +/- 0.45, N = 1331.0830.1530.6224.75MIN: 24.28 / MAX: 32.05MIN: 23.77 / MAX: 31.47MIN: 23.7 / MAX: 31.5MIN: 13.75 / MAX: 31.86
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50sbcd714212835Min: 23.99 / Avg: 24.75 / Max: 30.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152sbcd3691215SE +/- 0.02, N = 311.519.9310.979.79MIN: 9.43 / MAX: 12.68MIN: 5.85 / MAX: 12.52MIN: 9 / MAX: 12.55MIN: 7.71 / MAX: 9.95
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152sbcd3691215Min: 9.75 / Avg: 9.79 / Max: 9.81

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50sbcd48121620SE +/- 0.05, N = 314.2313.7813.7813.81MIN: 12.34 / MAX: 16.52MIN: 12.06 / MAX: 14.04MIN: 11.44 / MAX: 14MIN: 11.95 / MAX: 14.1
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50sbcd48121620Min: 13.74 / Avg: 13.81 / Max: 13.91

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50sbcd48121620SE +/- 0.10, N = 313.8613.6513.7913.53MIN: 12.24 / MAX: 14.1MIN: 11.36 / MAX: 13.96MIN: 12.26 / MAX: 13.98MIN: 7.72 / MAX: 13.95
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50sbcd48121620Min: 13.39 / Avg: 13.53 / Max: 13.73

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50sbcd48121620SE +/- 0.03, N = 313.8213.7513.7913.79MIN: 12.08 / MAX: 14.09MIN: 12.17 / MAX: 13.99MIN: 12.1 / MAX: 14.08MIN: 12.11 / MAX: 14.04
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50sbcd48121620Min: 13.74 / Avg: 13.79 / Max: 13.84

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152sbcd1.26682.53363.80045.06726.334SE +/- 0.04, N = 35.495.635.625.58MIN: 4.9 / MAX: 5.6MIN: 5.35 / MAX: 5.71MIN: 5.35 / MAX: 5.69MIN: 4.32 / MAX: 5.7
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152sbcd246810Min: 5.5 / Avg: 5.58 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50sbcd48121620SE +/- 0.12, N = 313.9013.7613.8113.68MIN: 10.84 / MAX: 14.08MIN: 9.38 / MAX: 13.97MIN: 11.69 / MAX: 14.05MIN: 11.92 / MAX: 14.02
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50sbcd48121620Min: 13.43 / Avg: 13.68 / Max: 13.83

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.575.585.615.62MIN: 4.59 / MAX: 5.66MIN: 4.83 / MAX: 5.65MIN: 5.32 / MAX: 5.68MIN: 4.5 / MAX: 5.69
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152sbcd246810Min: 5.6 / Avg: 5.62 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50sbcd48121620SE +/- 0.02, N = 313.8313.7413.8113.77MIN: 12.12 / MAX: 14.03MIN: 12.06 / MAX: 13.95MIN: 12.27 / MAX: 14.04MIN: 7.55 / MAX: 14.1
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50sbcd48121620Min: 13.73 / Avg: 13.77 / Max: 13.81

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.00, N = 35.545.615.615.62MIN: 5.28 / MAX: 5.59MIN: 5.34 / MAX: 5.67MIN: 5.32 / MAX: 5.68MIN: 5.31 / MAX: 5.71
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152sbcd246810Min: 5.62 / Avg: 5.62 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.555.605.595.62MIN: 4.7 / MAX: 5.67MIN: 4.17 / MAX: 5.67MIN: 5.31 / MAX: 5.66MIN: 5.19 / MAX: 5.7
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152sbcd246810Min: 5.61 / Avg: 5.62 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.565.595.595.62MIN: 4.51 / MAX: 5.64MIN: 5.31 / MAX: 5.66MIN: 4.43 / MAX: 5.65MIN: 3.95 / MAX: 5.71
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152sbcd246810Min: 5.6 / Avg: 5.62 / Max: 5.64

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lsbcd246810SE +/- 0.03, N = 37.377.327.367.33MIN: 5.71 / MAX: 7.46MIN: 5.07 / MAX: 7.42MIN: 6.88 / MAX: 7.43MIN: 5.29 / MAX: 7.45
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lsbcd3691215Min: 7.27 / Avg: 7.33 / Max: 7.37

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lsbcd0.92931.85862.78793.71724.6465SE +/- 0.00, N = 34.084.114.134.13MIN: 3.25 / MAX: 4.13MIN: 3.78 / MAX: 4.16MIN: 3.56 / MAX: 4.17MIN: 3.27 / MAX: 4.18
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lsbcd246810Min: 4.12 / Avg: 4.13 / Max: 4.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lsbcd0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.114.124.124.11MIN: 3.08 / MAX: 4.17MIN: 3.84 / MAX: 4.17MIN: 3.19 / MAX: 4.17MIN: 2.84 / MAX: 4.16
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lsbcd246810Min: 4.1 / Avg: 4.11 / Max: 4.12

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lsbcd0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.104.114.124.12MIN: 3.43 / MAX: 4.15MIN: 3.42 / MAX: 4.17MIN: 3.51 / MAX: 4.17MIN: 3.1 / MAX: 4.17
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lsbcd246810Min: 4.11 / Avg: 4.12 / Max: 4.12

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lsbcd0.92931.85862.78793.71724.6465SE +/- 0.00, N = 34.134.084.124.12MIN: 3.25 / MAX: 4.19MIN: 3.42 / MAX: 4.13MIN: 2.98 / MAX: 4.17MIN: 2.81 / MAX: 4.19
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lsbcd246810Min: 4.12 / Avg: 4.12 / Max: 4.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lsbcd0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.104.124.124.11MIN: 2.87 / MAX: 4.15MIN: 3.39 / MAX: 4.17MIN: 2.97 / MAX: 4.17MIN: 2.87 / MAX: 4.18
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lsbcd246810Min: 4.11 / Avg: 4.11 / Max: 4.12

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: CPU-Onlysbcd90180270360450SE +/- 0.10, N = 3417.28417.64416.74416.31
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: CPU-Onlysbcd70140210280350Min: 416.16 / Avg: 416.31 / Max: 416.49

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: CPU-Onlysbcd2004006008001000SE +/- 12.91, N = 41100.021103.331101.161113.84
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: CPU-Onlysbcd2004006008001000Min: 1098.07 / Avg: 1113.84 / Max: 1152.39

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: CPU-Onlysbcd110220330440550SE +/- 0.85, N = 3528.21528.72528.01528.78
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: CPU-Onlysbcd90180270360450Min: 527.17 / Avg: 528.78 / Max: 530.06

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: CPU-Onlysbcd30060090012001500SE +/- 1.37, N = 31401.881405.371401.131402.14
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: CPU-Onlysbcd2004006008001000Min: 1400.18 / Avg: 1402.14 / Max: 1404.78

s

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9
Python Notes: Python 3.10.12
Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 18 November 2023 14:00 by user pts.

b

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9
Python Notes: Python 3.10.12
Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 18 November 2023 16:20 by user pts.

c

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9
Python Notes: Python 3.10.12
Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 18 November 2023 18:59 by user pts.

d

Processor: Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads), Motherboard: Dell 0DXP1F (3.7.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Micron 2300 NVMe 512GB, Graphics: Intel Xe TGL GT2 15GB (1350MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

OS: Ubuntu 22.04, Kernel: 6.2.0-36-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 1920x1200

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9
Python Notes: Python 3.10.12
Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 18 November 2023 21:18 by user pts.