pytorch 2.2 raptor lake
Intel Core i9-14900K testing with a ASUS PRIME Z790-P WIFI (1402 BIOS) and ASUS Intel RPL-S 31GB on Ubuntu 23.10 via the Phoronix Test Suite.


a: 

	Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 2 x 16GB DRAM-6000MT/s Corsair CMK32GX5M2B6000C36, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: ASUS Intel RPL-S 31GB (1650MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U

	OS: Ubuntu 23.10, Kernel: 6.8.0-phx (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7, OpenGL: 4.6 Mesa 24.0~git2312240600.c05261~oibaf~m (git-c05261a 2023-12-24 mantic-oibaf-ppa), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160

b: 

	Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 2 x 16GB DRAM-6000MT/s Corsair CMK32GX5M2B6000C36, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: ASUS Intel RPL-S 31GB (1650MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U

	OS: Ubuntu 23.10, Kernel: 6.8.0-phx (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7, OpenGL: 4.6 Mesa 24.0~git2312240600.c05261~oibaf~m (git-c05261a 2023-12-24 mantic-oibaf-ppa), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160

c: 

	Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 2 x 16GB DRAM-6000MT/s Corsair CMK32GX5M2B6000C36, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: ASUS Intel RPL-S 31GB (1650MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U

	OS: Ubuntu 23.10, Kernel: 6.8.0-phx (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server 1.21.1.7, OpenGL: 4.6 Mesa 24.0~git2312240600.c05261~oibaf~m (git-c05261a 2023-12-24 mantic-oibaf-ppa), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160


PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 8.65  |===================================================
b . 11.62 |====================================================================
c . 10.40 |=============================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 8.54  |===================================================
b . 11.46 |====================================================================
c . 11.43 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 11.07 |=================================================================
b . 8.64  |===================================================
c . 11.54 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
a . 71.81 |====================================================================
b . 57.46 |======================================================
c . 57.44 |======================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 11.38 |====================================================================
b . 10.36 |==============================================================
c . 9.69  |==========================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 512 - Model: ResNet-152
batches/sec > Higher Is Better
a . 16.81 |====================================================================
b . 14.67 |===========================================================
c . 14.82 |============================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 512 - Model: ResNet-50
batches/sec > Higher Is Better
a . 39.63 |==============================================================
b . 38.43 |============================================================
c . 43.51 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-50
batches/sec > Higher Is Better
a . 43.57 |====================================================================
b . 38.83 |=============================================================
c . 42.44 |==================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-50
batches/sec > Higher Is Better
a . 43.57 |====================================================================
b . 43.69 |====================================================================
c . 39.10 |=============================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-152
batches/sec > Higher Is Better
a . 15.76 |================================================================
b . 16.66 |===================================================================
c . 16.85 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 11.15 |==================================================================
b . 11.53 |====================================================================
c . 11.47 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
a . 42.97 |==================================================================
b . 44.23 |====================================================================
c . 43.55 |===================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: ResNet-50
batches/sec > Higher Is Better
a . 43.62 |====================================================================
b . 42.96 |===================================================================
c . 43.70 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-152
batches/sec > Higher Is Better
a . 16.86 |====================================================================
b . 16.71 |===================================================================
c . 16.86 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
a . 28.55 |====================================================================
b . 28.35 |====================================================================
c . 28.47 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 12.93 |====================================================================
b . 13.00 |====================================================================
c . 13.02 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: ResNet-152
batches/sec > Higher Is Better
a . 16.87 |====================================================================
b . 16.79 |====================================================================
c . 16.80 |====================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
a . 16.82 |====================================================================
b . 16.83 |====================================================================
c . 16.82 |====================================================================