1080XE Linux
Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.30 BIOS) and NVIDIA NV132 11GB on Ubuntu 20.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2003275-NI-1080XELIN76.
toyBrot Fractal Generator
Implementation: OpenMP
toyBrot Fractal Generator
Implementation: C++ Tasks
toyBrot Fractal Generator
Implementation: C++ Threads
lzbench
Test: XZ 0 - Process: Compression
lzbench
Test: XZ 0 - Process: Decompression
lzbench
Test: Zstd 1 - Process: Compression
lzbench
Test: Zstd 1 - Process: Decompression
lzbench
Test: Zstd 8 - Process: Compression
lzbench
Test: Zstd 8 - Process: Decompression
lzbench
Test: Crush 0 - Process: Compression
lzbench
Test: Crush 0 - Process: Decompression
lzbench
Test: Brotli 0 - Process: Compression
lzbench
Test: Brotli 0 - Process: Decompression
lzbench
Test: Brotli 2 - Process: Compression
lzbench
Test: Brotli 2 - Process: Decompression
lzbench
Test: Libdeflate 1 - Process: Compression
lzbench
Test: Libdeflate 1 - Process: Decompression
SMHasher
Hash: wyhash
SMHasher
Hash: wyhash
SMHasher
Hash: MeowHash
SMHasher
Hash: MeowHash
SMHasher
Hash: Spooky32
SMHasher
Hash: Spooky32
SMHasher
Hash: fasthash32
SMHasher
Hash: fasthash32
SMHasher
Hash: t1ha2_atonce
SMHasher
Hash: t1ha2_atonce
SMHasher
Hash: t1ha0_aes_avx2
SMHasher
Hash: t1ha0_aes_avx2
FFTW
Build: Stock - Size: 1D FFT Size 32
FFTW
Build: Stock - Size: 1D FFT Size 64
FFTW
Build: Stock - Size: 2D FFT Size 32
FFTW
Build: Stock - Size: 2D FFT Size 64
FFTW
Build: Stock - Size: 1D FFT Size 128
FFTW
Build: Stock - Size: 1D FFT Size 256
FFTW
Build: Stock - Size: 1D FFT Size 512
FFTW
Build: Stock - Size: 2D FFT Size 128
FFTW
Build: Stock - Size: 2D FFT Size 256
FFTW
Build: Stock - Size: 2D FFT Size 512
FFTW
Build: Stock - Size: 1D FFT Size 1024
FFTW
Build: Stock - Size: 1D FFT Size 2048
FFTW
Build: Stock - Size: 1D FFT Size 4096
FFTW
Build: Stock - Size: 2D FFT Size 1024
FFTW
Build: Stock - Size: 2D FFT Size 2048
FFTW
Build: Stock - Size: 2D FFT Size 4096
FFTW
Build: Float + SSE - Size: 1D FFT Size 32
FFTW
Build: Float + SSE - Size: 1D FFT Size 64
FFTW
Build: Float + SSE - Size: 2D FFT Size 32
FFTW
Build: Float + SSE - Size: 2D FFT Size 64
FFTW
Build: Float + SSE - Size: 1D FFT Size 128
FFTW
Build: Float + SSE - Size: 1D FFT Size 256
FFTW
Build: Float + SSE - Size: 1D FFT Size 512
FFTW
Build: Float + SSE - Size: 2D FFT Size 128
FFTW
Build: Float + SSE - Size: 2D FFT Size 256
FFTW
Build: Float + SSE - Size: 2D FFT Size 512
FFTW
Build: Float + SSE - Size: 1D FFT Size 1024
FFTW
Build: Float + SSE - Size: 1D FFT Size 2048
FFTW
Build: Float + SSE - Size: 1D FFT Size 4096
FFTW
Build: Float + SSE - Size: 2D FFT Size 1024
FFTW
Build: Float + SSE - Size: 2D FFT Size 2048
FFTW
Build: Float + SSE - Size: 2D FFT Size 4096
MKL-DNN DNNL
Harness: IP Batch 1D - Data Type: f32
MKL-DNN DNNL
Harness: IP Batch All - Data Type: f32
MKL-DNN DNNL
Harness: IP Batch 1D - Data Type: u8s8f32
MKL-DNN DNNL
Harness: IP Batch All - Data Type: u8s8f32
MKL-DNN DNNL
Harness: IP Batch 1D - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: IP Batch All - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: Convolution Batch conv_3d - Data Type: f32
MKL-DNN DNNL
Harness: Convolution Batch conv_all - Data Type: f32
MKL-DNN DNNL
Harness: Convolution Batch conv_3d - Data Type: u8s8f32
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_1d - Data Type: f32
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_3d - Data Type: f32
MKL-DNN DNNL
Harness: Convolution Batch conv_alexnet - Data Type: f32
MKL-DNN DNNL
Harness: Convolution Batch conv_all - Data Type: u8s8f32
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_all - Data Type: f32
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32
MKL-DNN DNNL
Harness: Recurrent Neural Network Training - Data Type: f32
MKL-DNN DNNL
Harness: Convolution Batch conv_3d - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32
MKL-DNN DNNL
Harness: Convolution Batch conv_all - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_1d - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_3d - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: Convolution Batch conv_alexnet - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32
MKL-DNN DNNL
Harness: Deconvolution Batch deconv_all - Data Type: bf16bf16bf16
MKL-DNN DNNL
Harness: Convolution Batch conv_googlenet_v3 - Data Type: bf16bf16bf16
Timed GCC Compilation
Time To Compile
Timed LLVM Compilation
Time To Compile
LevelDB
Benchmark: Hot Read
LevelDB
Benchmark: Fill Sync
LevelDB
Benchmark: Fill Sync
LevelDB
Benchmark: Overwrite
LevelDB
Benchmark: Overwrite
LevelDB
Benchmark: Random Fill
LevelDB
Benchmark: Random Fill
LevelDB
Benchmark: Random Read
LevelDB
Benchmark: Seek Random
LevelDB
Benchmark: Random Delete
LevelDB
Benchmark: Sequential Fill
LevelDB
Benchmark: Sequential Fill
Facebook RocksDB
Test: Random Fill
Facebook RocksDB
Test: Random Read
Facebook RocksDB
Test: Sequential Fill
Facebook RocksDB
Test: Random Fill Sync
Facebook RocksDB
Test: Read While Writing
Numenta Anomaly Benchmark
Detector: EXPoSE
Numenta Anomaly Benchmark
Detector: Relative Entropy
Numenta Anomaly Benchmark
Detector: Windowed Gaussian
Numenta Anomaly Benchmark
Detector: Earthgecko Skyline
Numenta Anomaly Benchmark
Detector: Bayesian Changepoint
Phoronix Test Suite v10.8.5