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55First, run the benchmark.sh and verify_benchmark.sh scripts and pipe their output into `benchmark.py`
66and `verify_benchmark.py` respectively. If you submit the scripts as slurm jobs, this is done
7- automatically.
8-
9- The output is formatted like a Python dict, but you need to remove error and output messages. Then,
10- execute this script. It loads the outputs automatically.
7+ automatically. The output is formatted like a Python dict, but you need to remove error and output
8+ messages. Lastly, you need to copy the cycle frequency and the pipeline length from the reports into this script.
119"""
1210from matplotlib import pyplot
1311import numpy as np
1412
1513from benchmark import runtime
1614from verify_benchmark import value_derivation
1715
18- cycle_frequency = {
19- 225 : 79.63 * 10 ** 6 ,
20- }
21- pipeline_length = {
22- 225 : 225 ,
23- }
16+ cycle_frequency = 79.63 * 10 ** 6
17+ pipeline_length = 225
2418
2519height = width = 1024
2620radius = 1
4236 overhead = runtime [i ][0 ] - mean_delta
4337 print ("\t Overhead: {:.2f} seconds" .format (overhead ))
4438
45- executed_flop = pipeline_length [ i ] * flo_per_cell * height * width
46- executed_cycles = mean_delta * cycle_frequency [ i ]
39+ executed_flop = pipeline_length * flo_per_cell * height * width
40+ executed_cycles = mean_delta * cycle_frequency
4741
4842 gflops = executed_flop / mean_delta * 10 ** - 9
4943 ii = executed_cycles / (width * height )
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