Files
triton/autotune/python/optimize.py
Philippe Tillet 693b8b67b0 Dataset generation
2014-09-27 20:54:17 -04:00

54 lines
2.3 KiB
Python

import array
import numpy as np
import random
import sys
import itertools
import tools
import deap.tools
from genetic import GeneticOperators
#~ def parameter_space(operation):
#~ simd = [1, 2, 4, 8]
#~ pow2_1D = [2**k for k in range(12)]
#~ pow2_2D = [2**i for i in range(8)]
#~ pow2_2D_unrolled = [2**i for i in range(8)]
#~ FetchingPolicy = vcl.atidlas.FetchingPolicy
#~ fetch = [FetchingPolicy.FETCH_FROM_LOCAL, FetchingPolicy.FETCH_FROM_GLOBAL_CONTIGUOUS, FetchingPolicy.FETCH_FROM_GLOBAL_STRIDED]
#~ if operation == 'vector-axpy': return [simd, pow2_1D, pow2_1D, fetch]
#~ if operation == 'reduction': return [simd, pow2_1D, pow2_1D, fetch]
#~ if operation == 'matrix-axpy': return [simd, pow2_2D, pow2_2D, pow2_2D, pow2_2D, fetch]
#~ if operation == 'row-wise-reduction': return [simd, pow2_2D, pow2_2D, pow2_1D, fetch]
#~ if operation == 'matrix-product': return [simd, pow2_2D, pow2_2D, pow2_2D, pow2_2D_unrolled, pow2_2D_unrolled, pow2_2D_unrolled, fetch, fetch, [0] + pow2_2D, [0] + pow2_2D]
#~
#~ def exhaustive(statement, context, TemplateType, build_template, parameter_names, all_parameters, compute_perf, perf_metric, out):
#~ device = context.devices[0]
#~ nvalid = 0
#~ current = 0
#~ minT = float('inf')
#~ for individual in itertools.product(*all_parameters):
#~ template = build_template(TemplateType.Parameters(*individual))
#~ if not tools.skip(template, statement, device):
#~ nvalid = nvalid + 1
#~ for individual in itertools.product(*all_parameters):
#~ template = build_template(TemplateType.Parameters(*individual))
#~ try:
#~ T = tools.benchmark(template,statement,device)
#~ current = current + 1
#~ if T < minT:
#~ minT = T
#~ best = individual
#~ sys.stdout.write('%d / %d , Best is %d %s for %s\r'%(current, nvalid, compute_perf(minT), perf_metric, best))
#~ sys.stdout.flush()
#~ except:
#~ pass
#~ sys.stdout.write('\n')
#~ sys.stdout.flush()
#~
def genetic(statement, context, TemplateType, build_template, parameter_names, compute_perf, perf_metric, out):
GA = GeneticOperators(context.devices[0], statement, parameter_names, TemplateType, build_template, out)
GA.optimize(maxtime='2m30s', maxgen=1000, compute_perf=compute_perf, perf_metric=perf_metric)