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Use reordered, lossy bit handling

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Steven Robertson
2011-12-09 14:14:36 -05:00
parent b592cda3db
commit 6bac3b3a95
2 changed files with 35 additions and 24 deletions
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12
cuburn/render.py
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@ -8,6 +8,7 @@ from itertools import cycle, repeat, chain, izip
from ctypes import *
from cStringIO import StringIO
import numpy as np
from numpy import int32 as i32
from scipy import ndimage
from fr0stlib import pyflam3
@ -147,7 +148,9 @@ class Renderer(object):
d_log = cuda.mem_alloc(log_size * 4)
d_log_sorted = cuda.mem_alloc(log_size * 4)
sorter = sort.Sorter(log_size)
nwriteblocks = int(np.ceil(nbins / float(1<<12)))
# We need to cover each unique tag - address bits 20-23 - with one
# write block per sort bin. Or somethinig like that.
nwriteblocks = int(np.ceil(nbins / float(1<<20))) * 256
# Calculate 'nslots', the number of simultaneous running threads that
# can be active on the GPU during iteration (and thus the number of
@ -267,10 +270,11 @@ class Renderer(object):
block=(32, self._iter.NTHREADS/32, 1),
grid=(ntemporal_samples, 1), stream=iter_stream)
_sync_stream(write_stream, iter_stream)
sorter.sort(d_log_sorted, d_log, log_size, 12, True,
sorter.sort(d_log_sorted, d_log, log_size, 3, True,
stream=write_stream)
#print cuda.from_device(sorter.dglobal, (256,), np.uint32)
_sync_stream(iter_stream, write_stream)
write_fun(d_accum, d_log_sorted, sorter.dglobal,
write_fun(d_accum, d_log_sorted, sorter.dglobal, i32(nbins),
block=(1024, 1, 1), grid=(nwriteblocks, 1),
stream=write_stream)
else:
@ -302,5 +306,5 @@ class Renderer(object):
def _trim(self, result):
g = self.info.gutter
return result[g:-g,g:-g].copy()
return result[g:-g,g:g+self.info.width].copy()