def adjust_processing_time(num_cores, workload, timing, epoch):
 sigma = 0.0
 for i in range(num_cores):
  timing[i] = (workload[i] / (timing[i] - epoch))
  sigma += timing[i]
 spread = [None for x in range(num_cores)]
 for i in range(num_cores):
  spread[i] = ((timing[i] * num_cores) / sigma)
 return spread

def adjust_processing_time ( num_cores , workload , timing , epoch ) : sigma = 0.0 for i in range ( num_cores ) : timing [ i ] = ( workload [ i ] / ( timing [ i ] - epoch ) ) sigma += timing [ i ] spread = [ None for x in range ( num_cores ) ] for i in range ( num_cores ) : spread [ i ] = ( ( timing [ i ] * num_cores ) / sigma ) return spread
adjust processing time computes the nomalized relative worker throughput .