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opencl flac encoder

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chudov
2010-10-17 05:35:11 +00:00
parent 4a47615f7c
commit 349123ec19
2 changed files with 410 additions and 414 deletions
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744
CUETools.Codecs.FLACCL/FLACCLWriter.cs
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80
CUETools.Codecs.FLACCL/flac.cl
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@@ -449,8 +449,6 @@ void cudaQuantizeLPC(
}
}
#define BEACCURATE
__kernel /*__attribute__(( vec_type_hint (int4)))*/ __attribute__((reqd_work_group_size(GROUP_SIZE, 1, 1)))
void cudaEstimateResidual(
__global int*output,
@@ -460,12 +458,8 @@ void cudaEstimateResidual(
{
__local int data[GROUP_SIZE * 2];
__local FLACCLSubframeTask task;
#ifdef BEACCURATE
__local int residual[GROUP_SIZE];
__local int len[GROUP_SIZE / 16];
#else
__local float residual[GROUP_SIZE];
#endif
const int tid = get_local_id(0);
if (tid < sizeof(task)/sizeof(int))
@@ -477,12 +471,8 @@ void cudaEstimateResidual(
if (tid < 32 && tid >= ro)
task.coefs[tid] = 0;
#ifdef BEACCURATE
if (tid < GROUP_SIZE / 16)
len[tid] = 0;
#else
long res = 0;
#endif
data[tid] = 0;
barrier(CLK_LOCAL_MEM_FENCE);
@@ -495,6 +485,7 @@ void cudaEstimateResidual(
int4 cptr2 = cptr[2];
#endif
#endif
for (int pos = 0; pos < bs; pos += GROUP_SIZE)
{
// fetch samples
@@ -523,30 +514,33 @@ void cudaEstimateResidual(
#endif
;
int t = select(0, data[tid + GROUP_SIZE] - ((sum.x + sum.y + sum.z + sum.w) >> task.data.shift), offs >= ro && offs < bs);
#ifdef BEACCURATE
int t = data[tid + GROUP_SIZE] - ((sum.x + sum.y + sum.z + sum.w) >> task.data.shift);
// ensure we're within frame bounds
t = select(0, t, offs >= ro && offs < bs);
// overflow protection
t = clamp(t, -0x7fffff, 0x7fffff);
// convert to unsigned
residual[tid] = (t << 1) ^ (t >> 31);
#else
res += (t << 1) ^ (t >> 31);
#endif
barrier(CLK_GLOBAL_MEM_FENCE);
#ifdef BEACCURATE
// calculate rice partition bit length for every 16 samples
if (tid < GROUP_SIZE / 16)
{
__local int4 * chunk = ((__local int4 *)residual) + (tid << 2);
int4 sum = chunk[0] + chunk[1] + chunk[2] + chunk[3];
int res = sum.x + sum.y + sum.z + sum.w;
int k = clamp(27 - clz(res), 0, 14); // 27 - clz(res) == clz(16) - clz(res) == log2(res / 16)
#ifdef EXTRAMODE
sum = (chunk[0] >> k) + (chunk[1] >> k) + (chunk[2] >> k) + (chunk[3] >> k);
len[tid] += (k << 4) + sum.x + sum.y + sum.z + sum.w;
#else
len[tid] += (k << 4) + (res >> k);
}
#endif
}
data[tid] = nextData;
}
#ifdef BEACCURATE
barrier(CLK_LOCAL_MEM_FENCE);
for (int l = GROUP_SIZE / 32; l > 0; l >>= 1)
{
@@ -556,26 +550,6 @@ void cudaEstimateResidual(
}
if (tid == 0)
output[get_group_id(0)] = len[0] + (bs - ro);
#else
residual[tid] = res;
barrier(CLK_LOCAL_MEM_FENCE);
for (int l = GROUP_SIZE / 2; l > 0; l >>= 1)
{
if (tid < l)
residual[tid] += residual[tid + l];
barrier(CLK_LOCAL_MEM_FENCE);
}
if (tid == 0)
{
int residualLen = (bs - ro);
float sum = residual[0];// + residualLen / 2;
//int k = clamp(convert_int_rtn(log2((sum + 0.000001f) / (residualLen + 0.000001f))), 0, 14);
int k;
frexp((sum + 0.000001f) / residualLen, &k);
k = clamp(k - 1, 0, 14);
output[get_group_id(0)] = residualLen * (k + 1) + convert_int_rtn(min((float)0xffffff, sum / (1 << k)));
}
#endif
}
__kernel __attribute__((reqd_work_group_size(32, 1, 1)))
@@ -598,14 +572,14 @@ void cudaChooseBestMethod(
{
// fetch task data
if (tid < sizeof(task) / sizeof(int))
((__local int*)&task)[tid] = ((__global int*)(&tasks[taskNo + taskCount * get_group_id(1)].data))[tid];
((__local int*)&task)[tid] = ((__global int*)(&tasks[taskNo + taskCount * get_group_id(0)].data))[tid];
barrier(CLK_LOCAL_MEM_FENCE);
if (tid == 0)
{
// fetch part sum
int partLen = residual[taskNo + taskCount * get_group_id(1)];
int partLen = residual[taskNo + taskCount * get_group_id(0)];
//// calculate part size
//int residualLen = task[get_local_id(1)].data.blocksize - task[get_local_id(1)].data.residualOrder;
//residualLen = residualLen * (task[get_local_id(1)].data.type != Constant || psum != 0);
@@ -626,10 +600,10 @@ void cudaChooseBestMethod(
barrier(CLK_LOCAL_MEM_FENCE);
}
//shared.index[get_local_id(0)] = get_local_id(0);
//shared.length[get_local_id(0)] = (get_local_id(0) < taskCount) ? tasks[get_local_id(0) + taskCount * get_group_id(1)].size : 0x7fffffff;
//shared.length[get_local_id(0)] = (get_local_id(0) < taskCount) ? tasks[get_local_id(0) + taskCount * get_group_id(0)].size : 0x7fffffff;
if (tid < taskCount)
tasks[tid + taskCount * get_group_id(1)].data.size = shared.length[tid];
tasks[tid + taskCount * get_group_id(0)].data.size = shared.length[tid];
int l1 = shared.length[tid];
for (int l = 16; l > 0; l >>= 1)
@@ -643,7 +617,7 @@ void cudaChooseBestMethod(
barrier(CLK_LOCAL_MEM_FENCE);
}
if (tid == 0)
tasks[taskCount * get_group_id(1)].data.best_index = taskCount * get_group_id(1) + shared.index[0];
tasks[taskCount * get_group_id(0)].data.best_index = taskCount * get_group_id(0) + shared.index[0];
}
__kernel __attribute__((reqd_work_group_size(64, 1, 1)))
@@ -655,10 +629,10 @@ void cudaCopyBestMethod(
{
__local int best_index;
if (get_local_id(0) == 0)
best_index = tasks[count * get_group_id(1)].data.best_index;
best_index = tasks[count * get_group_id(0)].data.best_index;
barrier(CLK_LOCAL_MEM_FENCE);
if (get_local_id(0) < sizeof(FLACCLSubframeTask)/sizeof(int))
((__global int*)(tasks_out + get_group_id(1)))[get_local_id(0)] = ((__global int*)(tasks + best_index))[get_local_id(0)];
((__global int*)(tasks_out + get_group_id(0)))[get_local_id(0)] = ((__global int*)(tasks + best_index))[get_local_id(0)];
}
__kernel __attribute__((reqd_work_group_size(64, 1, 1)))
@@ -674,7 +648,7 @@ void cudaCopyBestMethodStereo(
int lr_index[2];
} shared;
if (get_local_id(0) < 4)
shared.best_index[get_local_id(0)] = tasks[count * (get_group_id(1) * 4 + get_local_id(0))].data.best_index;
shared.best_index[get_local_id(0)] = tasks[count * (get_group_id(0) * 4 + get_local_id(0))].data.best_index;
barrier(CLK_LOCAL_MEM_FENCE);
if (get_local_id(0) < 4)
shared.best_size[get_local_id(0)] = tasks[shared.best_index[get_local_id(0)]].data.size;
@@ -705,13 +679,13 @@ void cudaCopyBestMethodStereo(
}
barrier(CLK_LOCAL_MEM_FENCE);
if (get_local_id(0) < sizeof(FLACCLSubframeTask)/sizeof(int))
((__global int*)(tasks_out + 2 * get_group_id(1)))[get_local_id(0)] = ((__global int*)(tasks + shared.lr_index[0]))[get_local_id(0)];
((__global int*)(tasks_out + 2 * get_group_id(0)))[get_local_id(0)] = ((__global int*)(tasks + shared.lr_index[0]))[get_local_id(0)];
if (get_local_id(0) == 0)
tasks_out[2 * get_group_id(1)].data.residualOffs = tasks[shared.best_index[0]].data.residualOffs;
tasks_out[2 * get_group_id(0)].data.residualOffs = tasks[shared.best_index[0]].data.residualOffs;
if (get_local_id(0) < sizeof(FLACCLSubframeTask)/sizeof(int))
((__global int*)(tasks_out + 2 * get_group_id(1) + 1))[get_local_id(0)] = ((__global int*)(tasks + shared.lr_index[1]))[get_local_id(0)];
((__global int*)(tasks_out + 2 * get_group_id(0) + 1))[get_local_id(0)] = ((__global int*)(tasks + shared.lr_index[1]))[get_local_id(0)];
if (get_local_id(0) == 0)
tasks_out[2 * get_group_id(1) + 1].data.residualOffs = tasks[shared.best_index[1]].data.residualOffs;
tasks_out[2 * get_group_id(0) + 1].data.residualOffs = tasks[shared.best_index[1]].data.residualOffs;
}
// get_group_id(0) == task index
@@ -835,7 +809,7 @@ void cudaCalcPartition(
}
}
// get_group_id(1) == task index
// get_group_id(0) == task index
__kernel __attribute__((reqd_work_group_size(GROUP_SIZE, 1, 1)))
void cudaCalcPartition16(
__global int *partition_lengths,
@@ -851,7 +825,7 @@ void cudaCalcPartition16(
const int tid = get_local_id(0);
if (tid < sizeof(task) / sizeof(int))
((__local int*)&task)[tid] = ((__global int*)(&tasks[get_group_id(1)]))[tid];
((__local int*)&task)[tid] = ((__global int*)(&tasks[get_group_id(0)]))[tid];
barrier(CLK_LOCAL_MEM_FENCE);
int bs = task.data.blocksize;
@@ -921,7 +895,7 @@ void cudaCalcPartition16(
sum = (chunk[0] >> k) + (chunk[1] >> k) + (chunk[2] >> k) + (chunk[3] >> k);
s = sum.x + sum.y + sum.z + sum.w;
const int lpos = (15 << (max_porder + 1)) * get_group_id(1) + (k << (max_porder + 1)) + offs / 16;
const int lpos = (15 << (max_porder + 1)) * get_group_id(0) + (k << (max_porder + 1)) + offs / 16;
if (k <= 14)
partition_lengths[lpos] = min(0x7fffff, s) + (16 - select(0, ro, offs < 16)) * (k + 1);
}