8490h 1s

Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2307296-NE-8490H1S1663
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results

Limit displaying results to tests within:

CPU Massive 2 Tests
Creator Workloads 2 Tests
Database Test Suite 3 Tests
Multi-Core 2 Tests
Server 3 Tests
Common Workstation Benchmarks 2 Tests

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Geometric Means Per-Suite/Category
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
a
July 28 2023
  1 Hour, 52 Minutes
b
July 28 2023
  2 Hours, 53 Minutes
c
July 28 2023
  1 Hour, 26 Minutes
d
July 28 2023
  1 Hour, 25 Minutes
e
July 29 2023
  1 Hour, 25 Minutes
Invert Hiding All Results Option
  1 Hour, 48 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):

8490h 1s Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite. ,,"a","b","c","d","e" Processor,,Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads),Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads),Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads),Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads),Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads) Motherboard,,Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS),Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS),Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS),Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS),Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) Chipset,,Intel Device 1bce,Intel Device 1bce,Intel Device 1bce,Intel Device 1bce,Intel Device 1bce Memory,,512GB,512GB,512GB,512GB,512GB Disk,,3 x 3841GB Micron_9300_MTFDHAL3T8TDP,3 x 3841GB Micron_9300_MTFDHAL3T8TDP,3 x 3841GB Micron_9300_MTFDHAL3T8TDP,3 x 3841GB Micron_9300_MTFDHAL3T8TDP,3 x 3841GB Micron_9300_MTFDHAL3T8TDP Graphics,,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED Network,,4 x Intel E810-C for QSFP,4 x Intel E810-C for QSFP,4 x Intel E810-C for QSFP,4 x Intel E810-C for QSFP,4 x Intel E810-C for QSFP OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04 Kernel,,5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64) Desktop,,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4 Display Server,,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3 Vulkan,,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204 Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0 File-System,,ext4,ext4,ext4,ext4,ext4 Screen Resolution,,1024x768,1024x768,1024x768,1024x768,1024x768 ,,"a","b","c","d","e" "Apache Cassandra - Test: Writes (Op/s)",HIB,134694,134932,121708,140934,137849 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,2929613.17,2583878.29,2611551.59,2593991.1,2755166.14 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,759.4847,746.7073,758.3359,759.4253,709.1549 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,1.3144,1.3371,1.3167,1.3146,1.4076 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:1 (Ops/sec)",HIB,2503378.33,2630752.03,2460387.75,2493158.97,2474272.95 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,2613416.65,2546591.86,2516320.69,2452685.99,2444450.11 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,2627400.98,2710324.97,2554516.65,2549066.22,2541163.68 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,2646929.55,2544897.58,2508415.59,2487096.51,2540848.35 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,137.5084,133.779,135.9984,130.5153,137.7614 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,218.1115,224.1648,220.4888,229.4472,217.7184 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,534.5014,517.1634,517.8375,511.4186,520.2239 "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:1 (Ops/sec)",HIB,2462536.66,2470315.91,2377430.14,2383147.07,2414601.07 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,56.1193,57.7892,57.9253,58.2508,57.2121 "Dragonflydb - Clients Per Thread: 10 - Set To Get Ratio: 1:5 (Ops/sec)",HIB,14247982.45,14476834.10,14235868.61,14750102.52,14392511.79 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,117.2266,114.6147,116.3483,117.2235,113.2419 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,8.5248,8.7193,8.5903,8.5255,8.8247 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,121.8864,123.6781,124.6224,123.4543,120.4409 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,8.1989,8.0804,8.019,8.0945,8.2973 "Dragonflydb - Clients Per Thread: 10 - Set To Get Ratio: 1:10 (Ops/sec)",HIB,14662941.42,14292262.52,14204640.25,14205235.71,14390358.99 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,3.7271,3.6871,3.677,3.6743,3.7788 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,267.9943,270.8536,271.6229,271.7797,264.3062 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,475.7181,487.4646,487.1764,485.7154,488.2494 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,63.0065,61.5102,61.546,61.6935,61.4194 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,86.93,87.1582,86.786,87.3401,85.159 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,11.4928,11.4653,11.5118,11.4418,11.7345 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,184.3867,185.7453,184.1966,184.9319,181.1993 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.4182,5.3786,5.4239,5.402,5.5134 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,648.3175,644.0495,649.2977,648.3864,633.4455 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,46.2475,46.5440,46.1781,46.2436,47.3169 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,62.575,61.5956,61.4143,62.1748,61.0696 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (ms/batch)",LIB,3.6608,3.6961,3.7248,3.6938,3.7499 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (items/sec)",HIB,272.7991,270.2295,268.146,270.3481,266.3444 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,208.9561,209.1021,208.4283,209.6555,205.2428 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,4.7834,4.7802,4.7956,4.7675,4.8699 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (ms/batch)",LIB,47.2403,47.2504,47.4151,47.4732,48.2186 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (items/sec)",HIB,21.1647,21.1611,21.0871,21.0613,20.736 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,35.75,35.26,35.03,35.16,35.5 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,57.076,57.5702,57.9918,58.2129,57.5236 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,525.1385,520.8695,516.0418,514.8982,519.2686 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream (items/sec)",HIB,180.141,179.6816,178.7189,180.4386,177.0105 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.5454,5.5592,5.5886,5.5358,5.642 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,479.125,486.1851,488.2455,482.4354,488.2347 "Dragonflydb - Clients Per Thread: 10 - Set To Get Ratio: 1:100 (Ops/sec)",HIB,14338166.15,14432034.21,14307949.03,14571297.77,14492478.36 "BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,825917,823602,820410,812806,822977 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.4431,5.4340,5.4372,5.4307,5.5183 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,183.6332,183.9268,183.819,184.047,181.1289 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,68.93,69.16,70.03,69.16,69.25 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,35.4911,35.3613,35.6223,35.5925,35.0944 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,28.1702,28.2735,28.0659,28.0901,28.488 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,192.5033,191.9935,191.6104,190.8181,191.4971 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,155.8013,156.2109,156.4615,157.1756,156.5562 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,15.703,15.8316,15.8257,15.838,15.7168 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,88.73,88.5,88.83,88.18,88.09 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1905.9808,1891.0565,1891.327,1890.5705,1905.1491 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (ms/batch)",LIB,25.0015,24.9917,25.0071,25.0454,25.132 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (items/sec)",HIB,39.9427,39.9583,39.9318,39.8698,39.7368 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,780.3982,781.3024,780.3312,778.7629,782.5439 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,25.74,25.63,25.69,25.75,25.71 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,38.3944,38.3727,38.4054,38.4911,38.312 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,61.6472,61.8913,61.6088,61.8283,61.8458 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,16.2145,16.1504,16.2241,16.1666,16.1614 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,35.764,35.7199,35.8555,35.7569,35.8816 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,27.9552,27.9897,27.884,27.9607,27.8637 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,396.734,395.2099,396.6828,396.9936,396.1651 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,75.6034,75.8818,75.613,75.5523,75.7124 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,86.0393,85.9332,86.2759,86.2939,86.1261 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,86.4291,86.2508,86.1641,86.5253,86.1663 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,346.9388,347.6552,348.0117,346.5606,347.7604 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,38.4127,38.3371,38.4104,38.422,38.2796 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,780.4996,782.0400,780.5294,780.3141,783.198 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,348.5304,348.7206,347.5917,347.5128,348.1392 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,868.4975,869.4702,870.7567,871.2052,870.6664 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,272.91,273.14,272.64,272.41,272.44 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,34.4904,34.4634,34.4193,34.4017,34.4226 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,5672.7993,5678.5152,5677.035,5665.4699,5679.7805 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,5.268,5.2627,5.2632,5.2743,5.2615 "Crypto++ - Test: Unkeyed Algorithms (MiB/s)",HIB,452.343734,,,, "Crypto++ - Test: Keyed Algorithms (MiB/s)",HIB,595.365201,,,, "Crypto++ - Test: All Algorithms (MiB/s)",HIB,1663.920955,,,, "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10 ()",,,,,, "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5 ()",,,,,, "Redis 7.0.12 + memtier_benchmark - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:1 ()",,,,,, "Dragonflydb - Clients Per Thread: 20 - Set To Get Ratio: 1:100 ()",,,,,, "Dragonflydb - Clients Per Thread: 20 - Set To Get Ratio: 1:10 ()",,,,,, "Dragonflydb - Clients Per Thread: 20 - Set To Get Ratio: 1:5 ()",,,,,,