Table 5 Execution time for the third experiment on a heterogeneous standalone spark cluster with 3-VM workers across two machines
From: Instance segmentation on distributed deep learning big data cluster
Cluster Configuration: - Master VM in specs (7 GB RAM, Total processor cores = 8, HD = 130 GB)—Slave1 VM in specs (4.5 GB RAM, Total processor cores = 6, HD = 130 GB)—Master and Slave1 Processor: - 11th Gen Intel (R) Core (TM) i7-11370H @ 3.30 GHz—Slave2 VM in specs (6 GB RAM, Total processor cores=6, HD=130 GB)—Slave2 Processor: Intel (R) Core (TM) i7-3630QM CPU @ 2.40 GHz. And Spark cluster configured by driver-memory = 3 GB, num-executors = 3, executor-cores = 3, driver-cores = 3, executor-memory = 3GB | Spark cluster stand-alone stand-up time with 3 Executors | 63 s |
Total sum execution time for 35 images as one patch task job in 3 Executors | 4.43 min | |
Work executors in master VM processing time | 27 s | |
Work executors in slave2 VM processing time | 3.37 min | |
One Frame/image Processing time | 3.37*60 /35 = 5.77 s it calculated by the long executor time | |
WIFI speed on the local network | 130 Mbps |