1.0.0 System Test suite extracted from eMAG. pts/numpy-1.2.1 pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/avifenc-1.0.0 -s 0 Encoder Speed: 0 pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/build-eigen-1.1.0 Time To Compile pts/rav1e-1.4.0 -s 5 -l 60 Speed: 5 pts/avifenc-1.0.0 -s 2 Encoder Speed: 2 pts/rav1e-1.4.0 -s 6 -l 60 Speed: 6 pts/rav1e-1.4.0 -s 1 -l 20 Speed: 1 pts/stockfish-1.2.0 Total Time pts/asmfish-1.1.2 1024 Hash Memory, 26 Depth pts/rav1e-1.4.0 -s 10 -l 90 Speed: 10 pts/espeak-1.6.1 Text-To-Speech Synthesis pts/encode-ape-1.4.0 WAV To APE pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/simdjson-1.1.1 Kostya Throughput Test: Kostya pts/encode-opus-1.1.1 WAV To Opus Encode pts/clomp-1.1.1 Static OMP Speedup pts/simdjson-1.1.1 LargeRandom Throughput Test: LargeRandom pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/simdjson-1.1.1 PartialTweets Throughput Test: PartialTweets pts/simdjson-1.1.1 DistinctUserID Throughput Test: DistinctUserID pts/onednn-1.6.1 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/mafft-1.6.2 Multiple Sequence Alignment - LSU RNA pts/onednn-1.6.1 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/coremark-1.0.1 CoreMark Size 666 - Iterations Per Second pts/avifenc-1.0.0 -s 8 Encoder Speed: 8 pts/avifenc-1.0.0 -s 10 Encoder Speed: 10 pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/x264-2.6.1 H.264 Video Encoding pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/tscp-1.2.2 AI Chess Performance pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU