GCC 11 vs. LLVM Clang 12 Benchmarks On Xeon Ice Lake
Xeon Platinum 8380 compiler benchmarks by Michael Larabel looking at GCC 11 against LLVM Clang 12 for some initial holiday weekend tests...
HTML result view exported from: https://openbenchmarking.org/result/2105299-IB-COMPILERT91&grs&rdt.
NCNN
Target: CPU - Model: blazeface
NCNN
Target: CPU-v3-v3 - Model: mobilenet-v3
NCNN
Target: CPU-v2-v2 - Model: mobilenet-v2
C-Ray
Total Time - 4K, 16 Rays Per Pixel
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
OpenSSL
RSA 4096-bit Performance
TNN
Target: CPU - Model: MobileNet v2
ASTC Encoder
Preset: Medium
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ASTC Encoder
Preset: Thorough
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
Zstd Compression
Compression Level: 8, Long Mode - Compression Speed
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
Bullet Physics Engine
Test: 1000 Stack
Coremark
CoreMark Size 666 - Iterations Per Second
ASTC Encoder
Preset: Exhaustive
GraphicsMagick
Operation: Sharpen
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
Liquid-DSP
Threads: 160 - Buffer Length: 256 - Filter Length: 57
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
GraphicsMagick
Operation: Enhanced
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
WebP2 Image Encode
Encode Settings: Quality 100, Compression Effort 5
Himeno Benchmark
Poisson Pressure Solver
Opus Codec Encoding
WAV To Opus Encode
LAME MP3 Encoding
WAV To MP3
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
Bullet Physics Engine
Test: 3000 Fall
Kripke
Bullet Physics Engine
Test: 136 Ragdolls
NCNN
Target: CPU - Model: yolov4-tiny
Bullet Physics Engine
Test: 1000 Convex
Bullet Physics Engine
Test: Prim Trimesh
Bullet Physics Engine
Test: Convex Trimesh
oneDNN
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
x265
Video Input: Bosphorus 4K
WebP Image Encode
Encode Settings: Quality 100, Highest Compression
Crypto++
Test: Unkeyed Algorithms
WebP2 Image Encode
Encode Settings: Quality 95, Compression Effort 7
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
WebP2 Image Encode
Encode Settings: Quality 75, Compression Effort 7
TNN
Target: CPU - Model: SqueezeNet v1.1
AOBench
Size: 2048 x 2048 - Total Time
oneDNN
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
WebP2 Image Encode
Encode Settings: Default
SVT-HEVC
Tuning: 1 - Input: Bosphorus 1080p
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Very Fast
SVT-HEVC
Tuning: 7 - Input: Bosphorus 1080p
Zstd Compression
Compression Level: 8 - Compression Speed
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
Gcrypt Library
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
WebP Image Encode
Encode Settings: Quality 100, Lossless
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Very Fast
Zstd Compression
Compression Level: 19, Long Mode - Compression Speed
libjpeg-turbo tjbench
Test: Decompression Throughput
PostgreSQL pgbench
Scaling Factor: 100 - Clients: 250 - Mode: Read Write
PostgreSQL pgbench
Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency
SVT-VP9
Tuning: Visual Quality Optimized - Input: Bosphorus 1080p
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
WebP Image Encode
Encode Settings: Quality 100, Lossless, Highest Compression
WebP2 Image Encode
Encode Settings: Quality 100, Lossless Compression
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
Zstd Compression
Compression Level: 19 - Compression Speed
Timed MrBayes Analysis
Primate Phylogeny Analysis
SVT-VP9
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p
eSpeak-NG Speech Engine
Text-To-Speech Synthesis
SVT-VP9
Tuning: VMAF Optimized - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
WebP Image Encode
Encode Settings: Quality 100
Zstd Compression
Compression Level: 19 - Decompression Speed
Zstd Compression
Compression Level: 19, Long Mode - Decompression Speed
Liquid-DSP
Threads: 1 - Buffer Length: 256 - Filter Length: 57
WebP Image Encode
Encode Settings: Default
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
Primesieve
1e12 Prime Number Generation
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
Zstd Compression
Compression Level: 8 - Decompression Speed
Zstd Compression
Compression Level: 8, Long Mode - Decompression Speed
FLAC Audio Encoding
WAV To FLAC
x265
Video Input: Bosphorus 1080p
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
Caffe
Model: AlexNet - Acceleration: CPU - Iterations: 200
Caffe
Model: GoogleNet - Acceleration: CPU - Iterations: 200
SVT-HEVC
Tuning: 10 - Input: Bosphorus 1080p
WavPack Audio Encoding
WAV To WavPack
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
Darmstadt Automotive Parallel Heterogeneous Suite
Backend: OpenMP - Kernel: Euclidean Cluster
Darmstadt Automotive Parallel Heterogeneous Suite
Backend: OpenMP - Kernel: Points2Image
Darmstadt Automotive Parallel Heterogeneous Suite
Backend: OpenMP - Kernel: NDT Mapping
GraphicsMagick
Operation: Rotate
GNU GMP GMPbench
Total Time
NCNN
Target: CPU - Model: regnety_400m
NCNN
Target: CPU - Model: squeezenet_ssd
NCNN
Target: CPU - Model: resnet18
NCNN
Target: CPU - Model: vgg16
NCNN
Target: CPU - Model: googlenet
NCNN
Target: CPU - Model: efficientnet-b0
NCNN
Target: CPU - Model: mnasnet
NCNN
Target: CPU - Model: shufflenet-v2
NCNN
Target: CPU - Model: mobilenet
PostgreSQL pgbench
Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency
PostgreSQL pgbench
Scaling Factor: 100 - Clients: 250 - Mode: Read Only
GraphicsMagick
Operation: Resizing
Phoronix Test Suite v10.8.5