dwq AMD Ryzen 7 4700U testing with a LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS) and AMD Renoir 512MB on Ubuntu 22.04 via the Phoronix Test Suite. w: Processor: AMD Ryzen 7 4700U @ 2.00GHz (8 Cores), Motherboard: LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 512GB SAMSUNG MZALQ512HALU-000L2, Graphics: AMD Renoir 512MB (1600/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Intel Wi-Fi 6 AX200 OS: Ubuntu 22.04, Kernel: 5.18.8-051808-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.5 (LLVM 13.0.1 DRM 3.46), Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1080 b: Processor: AMD Ryzen 7 4700U @ 2.00GHz (8 Cores), Motherboard: LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 512GB SAMSUNG MZALQ512HALU-000L2, Graphics: AMD Renoir 512MB (1600/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Intel Wi-Fi 6 AX200 OS: Ubuntu 22.04, Kernel: 5.18.8-051808-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.5 (LLVM 13.0.1 DRM 3.46), Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1080 c: Processor: AMD Ryzen 7 4700U @ 2.00GHz (8 Cores), Motherboard: LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 512GB SAMSUNG MZALQ512HALU-000L2, Graphics: AMD Renoir 512MB (1600/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Intel Wi-Fi 6 AX200 OS: Ubuntu 22.04, Kernel: 5.18.8-051808-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.5 (LLVM 13.0.1 DRM 3.46), Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1080 OpenEMS 0.0.35-86 Test: pyEMS Coupler MCells/s > Higher Is Better w . 13.75 |==================================================================== b . 13.75 |==================================================================== c . 13.69 |==================================================================== ClickHouse 22.12.3.5 100M Rows Hits Dataset, Third Run Queries Per Minute, Geo Mean > Higher Is Better w . 69.29 |=================================================================== b . 70.02 |==================================================================== c . 68.41 |================================================================== ClickHouse 22.12.3.5 100M Rows Hits Dataset, Second Run Queries Per Minute, Geo Mean > Higher Is Better w . 69.58 |================================================================= b . 72.52 |==================================================================== c . 68.56 |================================================================ ClickHouse 22.12.3.5 100M Rows Hits Dataset, First Run / Cold Cache Queries Per Minute, Geo Mean > Higher Is Better w . 59.58 |================================================================= b . 58.54 |================================================================ c . 61.90 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 2000 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 23.18 |=================================================================== b . 23.69 |==================================================================== c . 22.98 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 2000 - Inner Join Test Time Seconds < Lower Is Better w . 25.39 |================================================================== b . 26.26 |==================================================================== c . 25.77 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 2000 - Repartition Test Time Seconds < Lower Is Better w . 21.91 |==================================================================== b . 21.37 |================================================================== c . 21.48 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 2000 - Group By Test Time Seconds < Lower Is Better w . 14.47 |================================================================= b . 15.03 |==================================================================== c . 14.79 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 21.77 |==================================================================== b . 21.83 |==================================================================== c . 21.85 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark Seconds < Lower Is Better w . 302.68 |=================================================================== b . 303.09 |=================================================================== c . 299.25 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 2000 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 28.98 |================================================================== b . 29.63 |==================================================================== c . 29.83 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 100 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 24.52 |==================================================================== b . 24.12 |=================================================================== c . 24.22 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 100 - Inner Join Test Time Seconds < Lower Is Better w . 24.29 |==================================================================== b . 24.29 |==================================================================== c . 23.64 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 100 - Repartition Test Time Seconds < Lower Is Better w . 21.46 |==================================================================== b . 21.60 |==================================================================== c . 21.39 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 100 - Group By Test Time Seconds < Lower Is Better w . 14.28 |==================================================================== b . 13.91 |================================================================== c . 14.24 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 21.94 |==================================================================== b . 21.91 |==================================================================== c . 21.62 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark Seconds < Lower Is Better w . 302.65 |=================================================================== b . 302.48 |=================================================================== c . 297.54 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 100 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 31.04 |==================================================================== b . 30.87 |==================================================================== c . 30.88 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 1000 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 22.47 |=================================================================== b . 22.89 |==================================================================== c . 22.22 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 1000 - Inner Join Test Time Seconds < Lower Is Better w . 23.93 |=================================================================== b . 24.30 |==================================================================== c . 23.76 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 1000 - Repartition Test Time Seconds < Lower Is Better w . 21.28 |==================================================================== b . 21.07 |=================================================================== c . 20.67 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 1000 - Group By Test Time Seconds < Lower Is Better w . 13.33 |================================================================== b . 13.79 |==================================================================== c . 13.64 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 22.00 |==================================================================== b . 21.72 |=================================================================== c . 21.71 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark Seconds < Lower Is Better w . 301.90 |=================================================================== b . 302.31 |=================================================================== c . 303.28 |=================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 1000 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 28.69 |==================================================================== b . 28.54 |=================================================================== c . 28.77 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 500 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 21.54 |=================================================================== b . 21.96 |==================================================================== c . 21.80 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 500 - Inner Join Test Time Seconds < Lower Is Better w . 23.87 |=============================================================== b . 23.71 |=============================================================== c . 25.63 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 500 - Repartition Test Time Seconds < Lower Is Better w . 20.78 |================================================================ b . 21.96 |==================================================================== c . 20.63 |================================================================ Apache Spark 3.3 Row Count: 10000000 - Partitions: 500 - Group By Test Time Seconds < Lower Is Better w . 12.70 |================================================================== b . 13.09 |==================================================================== c . 13.00 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 21.74 |==================================================================== b . 21.75 |==================================================================== c . 21.81 |==================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark Seconds < Lower Is Better w . 302.54 |=================================================================== b . 302.88 |=================================================================== c . 298.12 |================================================================== Apache Spark 3.3 Row Count: 10000000 - Partitions: 500 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 27.86 |================================================================== b . 28.47 |=================================================================== c . 28.70 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 5.00 |==================================================================== b . 5.08 |===================================================================== c . 4.70 |================================================================ Apache Spark 3.3 Row Count: 1000000 - Partitions: 2000 - Inner Join Test Time Seconds < Lower Is Better w . 6.230323969 |============================================================= b . 6.330000000 |============================================================== c . 6.060000000 |=========================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 2000 - Repartition Test Time Seconds < Lower Is Better w . 5.92 |==================================================================== b . 6.05 |===================================================================== c . 6.00 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 2000 - Group By Test Time Seconds < Lower Is Better w . 7.75 |=================================================================== b . 7.57 |================================================================== c . 7.97 |===================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 21.70 |==================================================================== b . 21.61 |=================================================================== c . 21.83 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Seconds < Lower Is Better w . 302.42 |=================================================================== b . 303.38 |=================================================================== c . 298.15 |================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 7.74 |===================================================================== b . 7.59 |==================================================================== c . 7.65 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 3.98 |=================================================================== b . 4.04 |==================================================================== c . 4.08 |===================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 1000 - Inner Join Test Time Seconds < Lower Is Better w . 4.66 |=================================================================== b . 4.75 |==================================================================== c . 4.79 |===================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 1000 - Repartition Test Time Seconds < Lower Is Better w . 5.53 |===================================================================== b . 5.46 |==================================================================== c . 5.47 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 1000 - Group By Test Time Seconds < Lower Is Better w . 6.80 |==================================================================== b . 6.82 |==================================================================== c . 6.92 |===================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 21.77 |==================================================================== b . 21.79 |==================================================================== c . 21.75 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Seconds < Lower Is Better w . 303.17 |=================================================================== b . 302.47 |=================================================================== c . 297.72 |================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 7.16 |===================================================================== b . 6.73 |================================================================= c . 6.93 |=================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 3.45 |==================================================================== b . 3.48 |===================================================================== c . 3.33 |================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 500 - Inner Join Test Time Seconds < Lower Is Better w . 3.98 |================================================================== b . 4.16 |===================================================================== c . 4.09 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 500 - Repartition Test Time Seconds < Lower Is Better w . 5.03 |===================================================================== b . 4.97 |==================================================================== c . 4.91 |=================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 500 - Group By Test Time Seconds < Lower Is Better w . 6.52 |===================================================================== b . 6.19 |================================================================== c . 6.40 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 21.78 |==================================================================== b . 21.77 |==================================================================== c . 21.73 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Seconds < Lower Is Better w . 303.10 |=================================================================== b . 302.82 |=================================================================== c . 297.89 |================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 6.09 |=================================================================== b . 6.03 |================================================================== c . 6.29 |===================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time Seconds < Lower Is Better w . 2.85 |================================================================= b . 3.01 |===================================================================== c . 2.79 |================================================================ Apache Spark 3.3 Row Count: 1000000 - Partitions: 100 - Inner Join Test Time Seconds < Lower Is Better w . 3.42 |==================================================================== b . 3.47 |===================================================================== c . 3.42 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 100 - Repartition Test Time Seconds < Lower Is Better w . 4.56 |============================================================= b . 5.13 |===================================================================== c . 4.63 |============================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 100 - Group By Test Time Seconds < Lower Is Better w . 5.916823945 |============================================================== b . 5.740000000 |============================================================ c . 5.840000000 |============================================================= Apache Spark 3.3 Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe Seconds < Lower Is Better w . 21.78 |==================================================================== b . 21.70 |==================================================================== c . 21.64 |==================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Seconds < Lower Is Better w . 301.78 |=================================================================== b . 302.67 |=================================================================== c . 298.32 |================================================================== Apache Spark 3.3 Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time Seconds < Lower Is Better w . 5.78 |==================================================================== b . 5.88 |===================================================================== c . 5.75 |=================================================================== KeyDB 6.3.2 Test: HMSET - Parallel Connections: 100 Requests Per Second > Higher Is Better w . 197850.55 |================================================================ b . 195504.95 |=============================================================== c . 196921.72 |================================================================ KeyDB 6.3.2 Test: HMSET - Parallel Connections: 50 Requests Per Second > Higher Is Better w . 243997.66 |================================================================ b . 241013.80 |=============================================================== c . 242171.80 |================================================================ KeyDB 6.3.2 Test: LPUSH - Parallel Connections: 100 Requests Per Second > Higher Is Better w . 289256.44 |================================================================ b . 275570.16 |============================================================= c . 277451.00 |============================================================= KeyDB 6.3.2 Test: SET - Parallel Connections: 100 Requests Per Second > Higher Is Better w . 292498.59 |============================================================== b . 301326.44 |================================================================ c . 284728.31 |============================================================ KeyDB 6.3.2 Test: LPOP - Parallel Connections: 100 Requests Per Second > Higher Is Better w . 310788.72 |================================================================ b . 290178.06 |============================================================ c . 286449.25 |=========================================================== KeyDB 6.3.2 Test: SADD - Parallel Connections: 100 Requests Per Second > Higher Is Better w . 303482.78 |================================================================ b . 303680.00 |================================================================ c . 301431.81 |================================================================ KeyDB 6.3.2 Test: GET - Parallel Connections: 100 Requests Per Second > Higher Is Better w . 307768.06 |================================================================ b . 298655.44 |============================================================== c . 309797.03 |================================================================ KeyDB 6.3.2 Test: LPUSH - Parallel Connections: 50 Requests Per Second > Higher Is Better w . 322162.88 |================================================================ b . 322381.00 |================================================================ c . 322966.12 |================================================================ PostgreSQL 15 Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency ms < Lower Is Better w . 256.70 |======================================================== b . 281.36 |============================================================= c . 307.22 |=================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 1000 - Mode: Read Write TPS > Higher Is Better w . 3896 |===================================================================== b . 3554 |=============================================================== c . 3255 |========================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency ms < Lower Is Better w . 215.87 |============================================================== b . 227.18 |================================================================== c . 231.52 |=================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 800 - Mode: Read Write TPS > Higher Is Better w . 3706 |===================================================================== b . 3522 |================================================================== c . 3455 |================================================================ PostgreSQL 15 Scaling Factor: 100 - Clients: 1 - Mode: Read Only - Average Latency ms < Lower Is Better w . 0.061 |==================================================================== b . 0.057 |================================================================ c . 0.060 |=================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 1 - Mode: Read Only TPS > Higher Is Better w . 16470 |================================================================ b . 17573 |==================================================================== c . 16675 |================================================================= PostgreSQL 15 Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency ms < Lower Is Better w . 9.224 |================================================================== b . 9.449 |==================================================================== c . 7.997 |========================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 1000 - Mode: Read Only TPS > Higher Is Better w . 108416 |========================================================== b . 105826 |========================================================= c . 125042 |=================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency ms < Lower Is Better w . 118.57 |=================================================== b . 133.56 |========================================================= c . 156.49 |=================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 500 - Mode: Read Write TPS > Higher Is Better w . 4217 |===================================================================== b . 3744 |============================================================= c . 3195 |==================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency ms < Lower Is Better w . 23.29 |============================================== b . 34.09 |==================================================================== c . 28.27 |======================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 100 - Mode: Read Write TPS > Higher Is Better w . 4294 |===================================================================== b . 2933 |=============================================== c . 3538 |========================================================= PostgreSQL 15 Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency ms < Lower Is Better w . 55.42 |======================================================= b . 65.70 |================================================================= c . 68.84 |==================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 250 - Mode: Read Write TPS > Higher Is Better w . 4511 |===================================================================== b . 3805 |========================================================== c . 3632 |======================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency ms < Lower Is Better w . 7.342 |==================================================================== b . 6.489 |============================================================ c . 6.856 |=============================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 800 - Mode: Read Only TPS > Higher Is Better w . 108957 |=========================================================== b . 123277 |=================================================================== c . 116684 |=============================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency ms < Lower Is Better w . 1.795 |==================================================================== b . 1.673 |=============================================================== c . 1.786 |==================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 250 - Mode: Read Only TPS > Higher Is Better w . 139280 |============================================================== b . 149428 |=================================================================== c . 139973 |=============================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 50 - Mode: Read Write - Average Latency ms < Lower Is Better w . 14.96 |============================================================= b . 16.08 |================================================================== c . 16.58 |==================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 50 - Mode: Read Write TPS > Higher Is Better w . 3343 |===================================================================== b . 3110 |================================================================ c . 3015 |============================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency ms < Lower Is Better w . 3.679 |================================================================= b . 3.519 |============================================================== c . 3.872 |==================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 500 - Mode: Read Only TPS > Higher Is Better w . 135920 |================================================================ b . 142097 |=================================================================== c . 129129 |============================================================= PostgreSQL 15 Scaling Factor: 100 - Clients: 1 - Mode: Read Write - Average Latency ms < Lower Is Better w . 3.539 |==================================================================== b . 3.368 |================================================================= c . 3.312 |================================================================ PostgreSQL 15 Scaling Factor: 100 - Clients: 1 - Mode: Read Write TPS > Higher Is Better w . 283 |================================================================== b . 297 |===================================================================== c . 302 |====================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency ms < Lower Is Better w . 0.511 |==================================================================== b . 0.487 |================================================================= c . 0.497 |================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 100 - Mode: Read Only TPS > Higher Is Better w . 195722 |================================================================ b . 205277 |=================================================================== c . 201277 |================================================================== KeyDB 6.3.2 Test: LPOP - Parallel Connections: 50 Requests Per Second > Higher Is Better w . 364758.50 |================================================================ b . 328344.66 |========================================================== c . 329246.28 |========================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 50 - Mode: Read Only - Average Latency ms < Lower Is Better w . 0.207 |================================================================== b . 0.206 |================================================================== c . 0.213 |==================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 50 - Mode: Read Only TPS > Higher Is Better w . 241562 |=================================================================== b . 242936 |=================================================================== c . 234435 |================================================================= KeyDB 6.3.2 Test: SET - Parallel Connections: 50 Requests Per Second > Higher Is Better w . 342479.81 |================================================================ b . 343064.97 |================================================================ c . 343137.91 |================================================================ KeyDB 6.3.2 Test: SADD - Parallel Connections: 50 Requests Per Second > Higher Is Better w . 360976.94 |================================================================ b . 355499.94 |=============================================================== c . 360394.12 |================================================================ KeyDB 6.3.2 Test: GET - Parallel Connections: 50 Requests Per Second > Higher Is Better w . 369786.94 |================================================================ b . 360287.66 |============================================================== c . 357666.59 |============================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 1000 - Mode: Read Write - Average Latency ms < Lower Is Better w . 4714.57 |================================================================= b . 4466.60 |============================================================== c . 4781.45 |================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 1000 - Mode: Read Write TPS > Higher Is Better w . 212 |================================================================== b . 224 |====================================================================== c . 209 |================================================================= PostgreSQL 15 Scaling Factor: 1 - Clients: 800 - Mode: Read Write - Average Latency ms < Lower Is Better w . 3731.90 |================================================================== b . 3547.23 |=============================================================== c . 3536.00 |=============================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 800 - Mode: Read Write TPS > Higher Is Better w . 214 |================================================================== b . 226 |====================================================================== c . 226 |====================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 500 - Mode: Read Write - Average Latency ms < Lower Is Better w . 1890.80 |================================================================== b . 1774.02 |============================================================== c . 1820.51 |================================================================ PostgreSQL 15 Scaling Factor: 1 - Clients: 500 - Mode: Read Write TPS > Higher Is Better w . 264 |================================================================== b . 282 |====================================================================== c . 275 |==================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 250 - Mode: Read Write - Average Latency ms < Lower Is Better w . 825.92 |================================================================== b . 758.75 |============================================================= c . 833.69 |=================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 250 - Mode: Read Write TPS > Higher Is Better w . 303 |================================================================ b . 329 |====================================================================== c . 300 |================================================================ PostgreSQL 15 Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency ms < Lower Is Better w . 288.67 |================================================================ b . 293.81 |================================================================= c . 302.13 |=================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 100 - Mode: Read Write TPS > Higher Is Better w . 346 |====================================================================== b . 340 |===================================================================== c . 331 |=================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency ms < Lower Is Better w . 142.68 |============================================================= b . 155.62 |=================================================================== c . 149.05 |================================================================ PostgreSQL 15 Scaling Factor: 1 - Clients: 50 - Mode: Read Write TPS > Higher Is Better w . 350 |====================================================================== b . 321 |================================================================ c . 335 |=================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency ms < Lower Is Better w . 0.448 |============================================================== b . 0.474 |================================================================== c . 0.491 |==================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 100 - Mode: Read Only TPS > Higher Is Better w . 223266 |=================================================================== b . 211074 |=============================================================== c . 203493 |============================================================= PostgreSQL 15 Scaling Factor: 1 - Clients: 800 - Mode: Read Only - Average Latency ms < Lower Is Better w . 6.422 |=================================================================== b . 6.125 |================================================================ c . 6.516 |==================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 800 - Mode: Read Only TPS > Higher Is Better w . 124581 |================================================================ b . 130604 |=================================================================== c . 122771 |=============================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 500 - Mode: Read Only - Average Latency ms < Lower Is Better w . 3.247 |============================================================ b . 3.690 |==================================================================== c . 3.517 |================================================================= PostgreSQL 15 Scaling Factor: 1 - Clients: 500 - Mode: Read Only TPS > Higher Is Better w . 153975 |=================================================================== b . 135518 |=========================================================== c . 142167 |============================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 1 - Mode: Read Only - Average Latency ms < Lower Is Better w . 0.057 |==================================================================== b . 0.051 |============================================================= c . 0.052 |============================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 1 - Mode: Read Only TPS > Higher Is Better w . 17392 |============================================================ b . 19564 |==================================================================== c . 19252 |=================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 1000 - Mode: Read Only - Average Latency ms < Lower Is Better w . 8.099 |==================================================================== b . 7.896 |================================================================== c . 7.897 |================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 1000 - Mode: Read Only TPS > Higher Is Better w . 123473 |================================================================= b . 126652 |=================================================================== c . 126633 |=================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 1 - Mode: Read Write - Average Latency ms < Lower Is Better w . 3.168 |==================================================================== b . 2.970 |================================================================ c . 3.028 |================================================================= PostgreSQL 15 Scaling Factor: 1 - Clients: 1 - Mode: Read Write TPS > Higher Is Better w . 316 |================================================================== b . 337 |====================================================================== c . 330 |===================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 250 - Mode: Read Only - Average Latency ms < Lower Is Better w . 1.590 |==================================================================== b . 1.068 |============================================== c . 1.582 |==================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 250 - Mode: Read Only TPS > Higher Is Better w . 157226 |============================================= b . 233976 |=================================================================== c . 158024 |============================================= PostgreSQL 15 Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency ms < Lower Is Better w . 0.195 |==================================================================== b . 0.191 |================================================================== c . 0.196 |==================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 50 - Mode: Read Only TPS > Higher Is Better w . 256079 |================================================================== b . 261198 |=================================================================== c . 255387 |================================================================== OpenEMS 0.0.35-86 Test: openEMS MSL_NotchFilter MCells/s > Higher Is Better w . 41.69 |==================================================================== b . 41.87 |==================================================================== c . 41.69 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 309.74 |=================================================================== b . 310.59 |=================================================================== c . 307.60 |================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 12.89 |==================================================================== b . 12.85 |=================================================================== c . 12.96 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 857.18 |================================================================== b . 864.26 |=================================================================== c . 856.22 |================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 4.6229 |=================================================================== b . 4.5919 |================================================================== c . 4.6467 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 81.95 |==================================================================== b . 82.07 |==================================================================== c . 82.14 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 48.79 |==================================================================== b . 48.72 |==================================================================== c . 48.65 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 880.90 |=================================================================== b . 879.99 |=================================================================== c . 884.08 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 4.5015 |=================================================================== b . 4.4905 |=================================================================== c . 4.4682 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 204.14 |================================================================== b . 205.28 |================================================================== c . 208.19 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 19.58 |==================================================================== b . 19.48 |==================================================================== c . 19.20 |=================================================================== Memcached 1.6.18 Set To Get Ratio: 1:10 Ops/sec > Higher Is Better w . 834672.86 |================================================================ b . 831515.24 |================================================================ c . 834811.61 |================================================================ Memcached 1.6.18 Set To Get Ratio: 1:5 Ops/sec > Higher Is Better w . 881038.49 |================================================================ b . 883520.20 |================================================================ c . 881419.05 |================================================================ Memcached 1.6.18 Set To Get Ratio: 1:100 Ops/sec > Higher Is Better w . 792731.89 |================================================================ b . 790452.45 |================================================================ c . 785762.34 |=============================================================== Neural Magic DeepSparse 1.3.2 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 761.63 |============================================================== b . 817.67 |=================================================================== c . 727.15 |============================================================ Neural Magic DeepSparse 1.3.2 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 5.2165 |================================================================ b . 4.8583 |=========================================================== c . 5.4834 |=================================================================== RocksDB 7.9.2 Test: Random Fill Sync Op/s > Higher Is Better w . 757 |===================================================================== b . 766 |====================================================================== c . 767 |====================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 77.90 |=================================================================== b . 76.60 |================================================================== c . 78.74 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 12.83 |=================================================================== b . 13.05 |==================================================================== c . 12.70 |================================================================== RocksDB 7.9.2 Test: Random Fill Op/s > Higher Is Better w . 569848 |=================================================================== b . 571727 |=================================================================== c . 560914 |================================================================== RocksDB 7.9.2 Test: Read While Writing Op/s > Higher Is Better w . 749177 |================================================================= b . 770192 |=================================================================== c . 754802 |================================================================== RocksDB 7.9.2 Test: Update Random Op/s > Higher Is Better w . 306010 |=================================================================== b . 304417 |=================================================================== c . 303583 |================================================================== RocksDB 7.9.2 Test: Read Random Write Random Op/s > Higher Is Better w . 791426 |================================================================== b . 796507 |=================================================================== c . 797910 |=================================================================== RocksDB 7.9.2 Test: Random Read Op/s > Higher Is Better w . 27294439 |================================================================= b . 27131130 |================================================================ c . 27452849 |================================================================= Neural Magic DeepSparse 1.3.2 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 27.33 |==================================================================== b . 27.13 |==================================================================== c . 26.88 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 36.57 |=================================================================== b . 36.84 |=================================================================== c . 37.19 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 211.76 |=================================================================== b . 211.95 |=================================================================== c . 213.01 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 4.7220 |=================================================================== b . 4.7178 |=================================================================== c . 4.6945 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 218.53 |================================================================= b . 226.38 |=================================================================== c . 223.46 |================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 4.5757 |=================================================================== b . 4.4172 |================================================================= c . 4.4749 |================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 58.07 |================================================================== b . 57.86 |================================================================== c . 59.77 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 17.22 |==================================================================== b . 17.28 |==================================================================== c . 16.73 |================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 187.97 |================================================================== b . 190.67 |=================================================================== c . 188.59 |================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 5.3194 |=================================================================== b . 5.2440 |================================================================== c . 5.3020 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 109.54 |================================================================== b . 111.26 |=================================================================== c . 110.66 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 36.48 |==================================================================== b . 35.89 |=================================================================== c . 36.13 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 153.62 |=================================================================== b . 149.30 |================================================================= c . 152.85 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 25.98 |================================================================== b . 26.73 |==================================================================== c . 26.12 |================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 5000 - Mode: Read Write TPS > Higher Is Better Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 30.96 |=================================================================== b . 31.49 |==================================================================== c . 30.62 |================================================================== Neural Magic DeepSparse 1.3.2 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 32.29 |=================================================================== b . 31.74 |================================================================== c . 32.65 |==================================================================== PostgreSQL 15 Scaling Factor: 100 - Clients: 5000 - Mode: Read Only TPS > Higher Is Better Neural Magic DeepSparse 1.3.2 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better w . 77.55 |==================================================================== b . 76.60 |=================================================================== c . 77.31 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better w . 51.49 |=================================================================== b . 52.15 |==================================================================== c . 51.66 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 45.67 |=================================================================== b . 45.53 |=================================================================== c . 46.26 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 21.89 |==================================================================== b . 21.96 |==================================================================== c . 21.61 |=================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better w . 21.54 |=================================================================== b . 21.71 |==================================================================== c . 21.61 |==================================================================== Neural Magic DeepSparse 1.3.2 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream items/sec > Higher Is Better w . 46.41 |==================================================================== b . 46.03 |=================================================================== c . 46.25 |==================================================================== RocksDB 7.9.2 Test: Sequential Fill Op/s > Higher Is Better w . 738360 |=================================================================== b . 731826 |================================================================== c . 728687 |================================================================== PostgreSQL 15 Scaling Factor: 1 - Clients: 5000 - Mode: Read Write TPS > Higher Is Better PostgreSQL 15 Scaling Factor: 1 - Clients: 5000 - Mode: Read Only TPS > Higher Is Better