Intel Xeon 6700E Sierra Forest vs. Ampere Altra vs. AMD EPYC

Ampere Altra versus Intel Sierra Forest benchmarks by Michael Larabel for a future article.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2406055-NE-INTELSRFA82
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C++ Boost Tests 2 Tests
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Database Test Suite 3 Tests
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HPC - High Performance Computing 6 Tests
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Multi-Core 14 Tests
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Performance Per
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Date
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  Test
  Duration
EPYC 8534P
May 18
  4 Hours, 34 Minutes
EPYC 8534PN
May 19
  4 Hours, 30 Minutes
EPYC 9654
May 13
  4 Hours, 32 Minutes
EPYC 9684X
May 12
  3 Hours, 49 Minutes
EPYC 9754
May 15
  4 Hours, 51 Minutes
Xeon 6766E
May 25
  4 Hours, 21 Minutes
Xeon 6780E
May 26
  4 Hours, 11 Minutes
Xeon Platinum 8380
May 09
  5 Hours, 57 Minutes
Xeon Platinum 8490H
April 16
  3 Hours, 45 Minutes
Xeon Platinum 8592+
April 11
  4 Hours, 57 Minutes
Xeon Max 9468
April 21
  5 Hours, 27 Minutes
Xeon Max 9480
April 26
  4 Hours, 23 Minutes
Ampere Altra Max M128-30
June 04
  8 Hours, 48 Minutes
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  4 Hours, 56 Minutes

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Intel Xeon 6700E Sierra Forest vs. Ampere Altra vs. AMD EPYC Suite 1.0.0 System Test suite extracted from Intel Xeon 6700E Sierra Forest vs. Ampere Altra vs. AMD EPYC. pts/build-linux-kernel-1.16.0 allmodconfig Build: allmodconfig pts/build-nodejs-1.4.0 Time To Compile pts/build-llvm-1.5.0 Ninja Build System: Ninja pts/openssl-3.3.0 sha256 Algorithm: SHA256 pts/openssl-3.3.0 sha512 Algorithm: SHA512 pts/john-the-ripper-1.8.0 --format=bcrypt Test: Blowfish pts/john-the-ripper-1.8.0 --format=bcrypt Test: bcrypt pts/clickhouse-1.2.0 100M Rows Hits Dataset, First Run / Cold Cache pts/clickhouse-1.2.0 100M Rows Hits Dataset, Second Run pts/clickhouse-1.2.0 100M Rows Hits Dataset, Third Run pts/pgbench-1.14.0 -s 100 -c 1000 Scaling Factor: 100 - Clients: 1000 - Mode: Read Write pts/pgbench-1.14.0 -s 100 -c 1000 Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency pts/pgbench-1.14.0 -s 100 -c 1000 -S Scaling Factor: 100 - Clients: 1000 - Mode: Read Only pts/pgbench-1.14.0 -s 100 -c 1000 -S Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency pts/rocksdb-1.6.0 --benchmarks="readrandom" Test: Random Read pts/rocksdb-1.6.0 --benchmarks="readwhilewriting" Test: Read While Writing pts/speedb-1.0.1 --benchmarks="readrandom" Test: Random Read pts/speedb-1.0.1 --benchmarks="readwhilewriting" Test: Read While Writing pts/coremark-1.0.1 CoreMark Size 666 - Iterations Per Second pts/mt-dgemm-1.2.0 Sustained Floating-Point Rate pts/m-queens-1.1.0 Time To Solve pts/minife-1.0.0 -‐nx 264 --ny 256 -‐nz 256 Problem Size: Small pts/cloverleaf-1.2.0 clover_bm64_short Input: clover_bm64_short pts/cloverleaf-1.2.0 clover_bm16 Input: clover_bm16 pts/quantlib-1.2.0 --mp Configuration: Multi-Threaded pts/compress-7zip-1.10.0 Test: Compression Rating pts/compress-7zip-1.10.0 Test: Decompression Rating pts/x265-1.4.0 Bosphorus_3840x2160.y4m Video Input: Bosphorus 4K pts/avifenc-1.4.1 -s 0 Encoder Speed: 0 pts/avifenc-1.4.1 -s 2 Encoder Speed: 2 pts/avifenc-1.4.1 -s 6 Encoder Speed: 6 pts/avifenc-1.4.1 -s 6 -l Encoder Speed: 6, Lossless pts/avifenc-1.4.1 -s 10 -l Encoder Speed: 10, Lossless pts/graphics-magick-2.2.0 -enhance Operation: Enhanced pts/liquid-dsp-1.6.0 -n 128 -b 256 -f 57 Threads: 128 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.6.0 -n 128 -b 256 -f 512 Threads: 128 - Buffer Length: 256 - Filter Length: 512 pts/liquid-dsp-1.6.0 -n 256 -b 256 -f 57 Threads: 256 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.6.0 -n 256 -b 256 -f 512 Threads: 256 - Buffer Length: 256 - Filter Length: 512 pts/srsran-2.3.0 tests/benchmarks/phy/upper/channel_processors/pdsch_processor_benchmark -m throughput_total -R 350 -B 10 -P 4port_4layer_scs30_100MHz_256qam Test: PDSCH Processor Benchmark, Throughput Total pts/pytorch-1.1.0 cpu 64 resnet50 Device: CPU - Batch Size: 64 - Model: ResNet-50 pts/pytorch-1.1.0 cpu 256 resnet50 Device: CPU - Batch Size: 256 - Model: ResNet-50 pts/pytorch-1.1.0 cpu 512 resnet50 Device: CPU - Batch Size: 512 - Model: ResNet-50 pts/openvino-1.5.0 -m models/intel/machine-translation-nar-en-de-0002/FP16/machine-translation-nar-en-de-0002.xml -d CPU Model: Machine Translation EN To DE FP16 - Device: CPU pts/openvino-1.5.0 -m models/intel/handwritten-english-recognition-0001/FP16-INT8/handwritten-english-recognition-0001.xml -d CPU Model: Handwritten English Recognition FP16-INT8 - Device: CPU pts/llamafile-1.1.0 run-llava --gpu DISABLE Test: llava-v1.5-7b-q4 - Acceleration: CPU pts/llamafile-1.1.0 run-wizardcoder --gpu DISABLE Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPU pts/xmrig-1.2.0 -a gr --bench=1M Variant: GhostRider - Hash Count: 1M pts/stockfish-1.5.0 Chess Benchmark