1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
|
#!/usr/bin/env python
#
# Project: Sift implementation in Python + OpenCL
# https://github.com/silx-kit/silx
#
# Copyright (C) 2022-2023 European Synchrotron Radiation Facility, Grenoble, France
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation
# files (the "Software"), to deal in the Software without
# restriction, including without limitation the rights to use,
# copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following
# conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
# OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
"""
This module provides a class for CBF byte offset compression/decompression.
"""
__authors__ = ["Jérôme Kieffer"]
__contact__ = "jerome.kieffer@esrf.eu"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "09/11/2022"
__status__ = "production"
import os
import struct
import numpy
from ..common import ocl, pyopencl, kernel_workgroup_size
from ..processing import BufferDescription, EventDescription, OpenclProcessing
import logging
logger = logging.getLogger(__name__)
class BitshuffleLz4(OpenclProcessing):
"""Perform the bitshuffle-lz4 decompression on the GPU
See :class:`OpenclProcessing` for optional arguments description.
:param int cmp_size:
Size of the raw stream for decompression.
It can be (slightly) larger than the array.
:param int dec_size:
Size of the decompression output array
(mandatory for decompression)
:param dtype: dtype of decompressed data
"""
LZ4_BLOCK_SIZE = 8192
def __init__(
self,
cmp_size,
dec_size,
dtype,
ctx=None,
devicetype="all",
platformid=None,
deviceid=None,
block_size=None,
profile=False,
):
"""Constructor of the class:
:param cmp_size: size of the compressed data buffer (in bytes)
:param dec_size: size of the compressed data buffer (in words)
:param dtype: data type of one work in decompressed array
For the other, see the doc of OpenclProcessing
"""
OpenclProcessing.__init__(
self,
ctx=ctx,
devicetype=devicetype,
platformid=platformid,
deviceid=deviceid,
block_size=block_size,
profile=profile,
)
if self.block_size is None:
try:
self.block_size = self.ctx.devices[0].preferred_work_group_size_multiple
except:
self.block_size = self.device.max_work_group_size
self.cmp_size = numpy.uint64(cmp_size)
self.dec_size = numpy.uint64(dec_size)
self.dec_dtype = numpy.dtype(dtype)
self.num_blocks = numpy.uint32(
(self.dec_dtype.itemsize * self.dec_size + self.LZ4_BLOCK_SIZE - 1)
// self.LZ4_BLOCK_SIZE
)
buffers = [
BufferDescription("nb_blocks", 1, numpy.uint32, None),
BufferDescription("block_position", self.num_blocks, numpy.uint64, None),
BufferDescription("cmp", self.cmp_size, numpy.uint8, None),
BufferDescription("dec", self.dec_size, self.dec_dtype, None),
]
self.allocate_buffers(buffers, use_array=True)
self.compile_kernels([os.path.join("codec", "bitshuffle_lz4")])
self.block_size = min(
self.block_size,
kernel_workgroup_size(self.program, "bslz4_decompress_block"),
)
def decompress(self, raw, out=None, wg=None, nbytes=None):
"""This function actually performs the decompression by calling the kernels
:param numpy.ndarray raw: The compressed data as a 1D numpy array of char or string
:param pyopencl.array out: pyopencl array in which to place the result.
:param wg: tuneable parameter with the workgroup size.
:param int nbytes: (Optional) Number of bytes occupied by the chunk in raw.
:return: The decompressed image as an pyopencl array.
:rtype: pyopencl.array
"""
events = []
with self.sem:
if nbytes is not None:
assert nbytes <= raw.size
len_raw = numpy.uint64(nbytes)
elif isinstance(raw, pyopencl.Buffer):
len_raw = numpy.uint64(raw.size)
else:
len_raw = numpy.uint64(len(raw))
if isinstance(raw, pyopencl.array.Array):
cmp_buffer = raw.data
num_blocks = self.num_blocks
elif isinstance(raw, pyopencl.Buffer):
cmp_buffer = raw
num_blocks = self.num_blocks
else:
if len_raw > self.cmp_size:
self.cmp_size = len_raw
logger.info("increase cmp buffer size to %s", self.cmp_size)
self.cl_mem["cmp"] = pyopencl.array.empty(
self.queue, self.cmp_size, dtype=numpy.uint8
)
evt = pyopencl.enqueue_copy(
self.queue, self.cl_mem["cmp"].data, raw, is_blocking=False
)
events.append(EventDescription("copy raw H -> D", evt))
cmp_buffer = self.cl_mem["cmp"].data
dest_size = struct.unpack(">Q", raw[:8])
self_dest_nbyte = self.dec_size * self.dec_dtype.itemsize
if dest_size < self_dest_nbyte:
num_blocks = numpy.uint32(
(dest_size + self.LZ4_BLOCK_SIZE - 1) // self.LZ4_BLOCK_SIZE
)
elif dest_size > self_dest_nbyte:
num_blocks = numpy.uint32(
(dest_size + self.LZ4_BLOCK_SIZE - 1) // self.LZ4_BLOCK_SIZE
)
self.cl_mem["dec"] = pyopencl.array.empty(
self.queue, dest_size, self.dec_dtype
)
self.dec_size = dest_size // self.dec_dtype.itemsize
else:
num_blocks = self.num_blocks
wg = int(wg or self.block_size)
evt = self.program.lz4_unblock(
self.queue,
(1,),
(1,),
cmp_buffer,
len_raw,
self.cl_mem["block_position"].data,
num_blocks,
self.cl_mem["nb_blocks"].data,
)
events.append(EventDescription("LZ4 unblock", evt))
if out is None:
out = self.cl_mem["dec"]
else:
assert out.dtype == self.dec_dtype
assert out.size == self.dec_size
evt = self.program.bslz4_decompress_block(
self.queue,
(self.num_blocks * wg,),
(wg,),
cmp_buffer,
out.data,
self.cl_mem["block_position"].data,
self.cl_mem["nb_blocks"].data,
numpy.uint8(self.dec_dtype.itemsize),
)
events.append(EventDescription("LZ4 decompress", evt))
self.profile_multi(events)
return out
__call__ = decompress
|
