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trying to do rice partitioning on gpu

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This commit is contained in:
chudov
2009-10-04 17:28:52 +00:00
parent 609f160457
commit d96ba46ad3
3 changed files with 222 additions and 166 deletions
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12
CUETools.FlaCuda/FlaCudaWriter.cs
View File

@@ -1192,11 +1192,12 @@ namespace CUETools.Codecs.FlaCuda
cuda.SetParameter(cudaCalcPartition, 0, (uint)task.cudaPartitions.Pointer); cuda.SetParameter(cudaCalcPartition, 0, (uint)task.cudaPartitions.Pointer);
cuda.SetParameter(cudaCalcPartition, 1 * sizeof(uint), (uint)task.cudaResidual.Pointer); cuda.SetParameter(cudaCalcPartition, 1 * sizeof(uint), (uint)task.cudaResidual.Pointer);
cuda.SetParameter(cudaCalcPartition, 2 * sizeof(uint), (uint)task.cudaBestResidualTasks.Pointer); cuda.SetParameter(cudaCalcPartition, 2 * sizeof(uint), (uint)task.cudaSamples.Pointer);
cuda.SetParameter(cudaCalcPartition, 3 * sizeof(uint), (uint)max_porder); cuda.SetParameter(cudaCalcPartition, 3 * sizeof(uint), (uint)task.cudaBestResidualTasks.Pointer);
cuda.SetParameter(cudaCalcPartition, 4 * sizeof(uint), (uint)calcPartitionPartSize); cuda.SetParameter(cudaCalcPartition, 4 * sizeof(uint), (uint)max_porder);
cuda.SetParameter(cudaCalcPartition, 5 * sizeof(uint), (uint)calcPartitionPartCount); cuda.SetParameter(cudaCalcPartition, 5 * sizeof(uint), (uint)calcPartitionPartSize);
cuda.SetParameterSize(cudaCalcPartition, 6U * sizeof(uint)); cuda.SetParameter(cudaCalcPartition, 6 * sizeof(uint), (uint)calcPartitionPartCount);
cuda.SetParameterSize(cudaCalcPartition, 7U * sizeof(uint));
cuda.SetFunctionBlockShape(cudaCalcPartition, 16, 16, 1); cuda.SetFunctionBlockShape(cudaCalcPartition, 16, 16, 1);
cuda.SetParameter(task.cudaSumPartition, 0, (uint)task.cudaPartitions.Pointer); cuda.SetParameter(task.cudaSumPartition, 0, (uint)task.cudaPartitions.Pointer);
@@ -1237,6 +1238,7 @@ namespace CUETools.Codecs.FlaCuda
if (!encode_on_cpu) if (!encode_on_cpu)
{ {
int bsz = calcPartitionPartCount * calcPartitionPartSize; int bsz = calcPartitionPartCount * calcPartitionPartSize;
if (cudaCalcPartition.Pointer != task.cudaCalcPartition.Pointer)
cuda.LaunchAsync(task.cudaEncodeResidual, residualPartCount, channels * task.frameCount, task.stream); cuda.LaunchAsync(task.cudaEncodeResidual, residualPartCount, channels * task.frameCount, task.stream);
cuda.LaunchAsync(cudaCalcPartition, (task.frameSize + bsz - 1) / bsz, channels * task.frameCount, task.stream); cuda.LaunchAsync(cudaCalcPartition, (task.frameSize + bsz - 1) / bsz, channels * task.frameCount, task.stream);
if (max_porder > 0) if (max_porder > 0)

42
CUETools.FlaCuda/flacuda.cu
View File

@@ -824,6 +824,7 @@ extern "C" __global__ void cudaEncodeResidual(
extern "C" __global__ void cudaCalcPartition( extern "C" __global__ void cudaCalcPartition(
int* partition_lengths, int* partition_lengths,
int* residual, int* residual,
int* samples,
encodeResidualTaskStruct *tasks, encodeResidualTaskStruct *tasks,
int max_porder, // <= 8 int max_porder, // <= 8
int psize, // == (shared.task.blocksize >> max_porder), < 256 int psize, // == (shared.task.blocksize >> max_porder), < 256
@@ -831,8 +832,7 @@ extern "C" __global__ void cudaCalcPartition(
) )
{ {
__shared__ struct { __shared__ struct {
int data[256]; int data[256+32];
int length[256];
encodeResidualTaskStruct task; encodeResidualTaskStruct task;
} shared; } shared;
const int tid = threadIdx.x + (threadIdx.y << 4); const int tid = threadIdx.x + (threadIdx.y << 4);
@@ -841,33 +841,50 @@ extern "C" __global__ void cudaCalcPartition(
__syncthreads(); __syncthreads();
const int parts = min(parts_per_block, (1 << max_porder) - blockIdx.x * parts_per_block); const int parts = min(parts_per_block, (1 << max_porder) - blockIdx.x * parts_per_block);
const int offs = blockIdx.x * psize * parts_per_block + tid;
// fetch residual // fetch samples
int offs = blockIdx.x * psize * parts_per_block + tid; if (tid < 32) shared.data[tid] = min(offs, tid + shared.task.residualOrder) >= 32 ? samples[shared.task.samplesOffs + offs - 32] >> shared.task.wbits : 0;
int s = (offs >= shared.task.residualOrder && tid < parts * psize) ? residual[shared.task.residualOffs + offs] : 0; shared.data[32 + tid] = tid < parts * psize ? samples[shared.task.samplesOffs + offs] >> shared.task.wbits : 0;
__syncthreads();
// compute residual
int s = 0;
for (int c = -shared.task.residualOrder; c < 0; c++)
s += __mul24(shared.data[32 + tid + c], shared.task.coefs[shared.task.residualOrder + c]);
s = shared.data[32 + tid] - (s >> shared.task.shift);
if (offs >= shared.task.residualOrder && tid < parts * psize)
residual[shared.task.residualOffs + offs] = s;
else
s = 0;
__syncthreads();
// convert to unsigned // convert to unsigned
shared.data[tid] = min(0xfffff, (s << 1) ^ (s >> 31)); shared.data[tid] = min(0xfffff, (s << 1) ^ (s >> 31));
__syncthreads(); __syncthreads();
int sum = 0; s = (psize - shared.task.residualOrder * (threadIdx.y + blockIdx.x == 0)) * (threadIdx.x + 1);
int dpos = threadIdx.y * psize; int dpos = threadIdx.y * psize;
// calc number of unary bits for each residual part with each rice paramater // calc number of unary bits for each residual part with each rice paramater
#pragma unroll 0 #pragma unroll 0
for (int i = 0; i < psize; i++) for (int i = 0; i < psize; i++)
// for part (threadIdx.y) with this rice paramater (threadIdx.x) // for part (threadIdx.y) with this rice paramater (threadIdx.x)
sum += shared.data[dpos + i] >> threadIdx.x; s += shared.data[dpos + i] >> threadIdx.x;
shared.length[tid] = sum + (psize - shared.task.residualOrder * (threadIdx.y + blockIdx.x == 0)) * (threadIdx.x + 1); __syncthreads();
shared.data[tid] = s;
__syncthreads(); __syncthreads();
// output length (transposed: k is now threadIdx.y) // output length (transposed: k is now threadIdx.y)
const int pos = (15 << (max_porder + 1)) * blockIdx.y + (threadIdx.y << (max_porder + 1)); const int pos = (15 << (max_porder + 1)) * blockIdx.y + (threadIdx.y << (max_porder + 1));
if (threadIdx.y <= 14 && threadIdx.x < parts) if (threadIdx.y <= 14 && threadIdx.x < parts)
partition_lengths[pos + blockIdx.x * parts_per_block + threadIdx.x] = shared.length[threadIdx.y + (threadIdx.x << 4)]; partition_lengths[pos + blockIdx.x * parts_per_block + threadIdx.x] = shared.data[threadIdx.y + (threadIdx.x << 4)];
} }
extern "C" __global__ void cudaCalcPartition1( extern "C" __global__ void cudaCalcPartition1(
int* partition_lengths, int* partition_lengths,
int* residual, int* residual,
int* samples,
encodeResidualTaskStruct *tasks, encodeResidualTaskStruct *tasks,
int max_porder, // <= 8 int max_porder, // <= 8
int psize, // == (shared.task.blocksize >> max_porder), < 256 int psize, // == (shared.task.blocksize >> max_porder), < 256
@@ -916,6 +933,7 @@ extern "C" __global__ void cudaCalcPartition1(
extern "C" __global__ void cudaCalcLargePartition( extern "C" __global__ void cudaCalcLargePartition(
int* partition_lengths, int* partition_lengths,
int* residual, int* residual,
int* samples,
encodeResidualTaskStruct *tasks, encodeResidualTaskStruct *tasks,
int max_porder, // <= 8 int max_porder, // <= 8
int psize, // == >= 128 int psize, // == >= 128
@@ -1016,16 +1034,18 @@ extern "C" __global__ void cudaFindRiceParameter(
shared.length[tid] = l1 = min(l1, l2); shared.length[tid] = l1 = min(l1, l2);
#pragma unroll 2 #pragma unroll 2
for (int sh = 2; sh > 0; sh --) for (int sh = 2; sh > 0; sh --)
if (threadIdx.x < (1 << sh))
{ {
l2 = shared.length[tid + (1 << sh)]; l2 = shared.length[tid + (1 << sh)];
shared.index[tid] = shared.index[tid + ((l2 < l1) << sh)]; shared.index[tid] = shared.index[tid + ((l2 < l1) << sh)];
shared.length[tid] = l1 = min(l1, l2); shared.length[tid] = l1 = min(l1, l2);
} }
if (threadIdx.x == 0 && threadIdx.y < parts)
{
l2 = shared.length[tid + 1]; l2 = shared.length[tid + 1];
if (threadIdx.x == 0 && threadIdx.y < parts)
shared.outidx[threadIdx.y] = shared.index[tid + (l2 < l1)]; shared.outidx[threadIdx.y] = shared.index[tid + (l2 < l1)];
if (threadIdx.x == 0 && threadIdx.y < parts)
shared.outlen[threadIdx.y] = min(l1, l2); shared.outlen[threadIdx.y] = min(l1, l2);
}
__syncthreads(); __syncthreads();
// output rice parameter // output rice parameter
if (tid < parts) if (tid < parts)

322
CUETools.FlaCuda/flacuda.cubin
View File

@@ -711,7 +711,7 @@ code {
code { code {
name = cudaCalcPartition1 name = cudaCalcPartition1
lmem = 0 lmem = 0
smem = 3304 smem = 3308
reg = 11 reg = 11
bar = 1 bar = 1
const { const {
@@ -731,67 +731,67 @@ code {
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0xd00e0201 0xa0c00781 0xd00e0201 0xa0c00781
} }
} }
@@ -1107,45 +1107,45 @@ code {
0xd808380d 0x20000780 0x1900ee18 0x1d00e004 0xd808380d 0x20000780 0x1900ee18 0x1d00e004
0x861ffe03 0x00000000 0x300603fd 0x6c0107c8 0x861ffe03 0x00000000 0x300603fd 0x6c0107c8
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0xd00e0201 0xa0c00781
} }
} }
code { code {
@@ -1417,76 +1417,110 @@ code {
code { code {
name = cudaCalcPartition name = cudaCalcPartition
lmem = 0 lmem = 0
smem = 2280 smem = 1388
reg = 12 reg = 11
bar = 1 bar = 1
const { const {
segname = const segname = const
segnum = 1 segnum = 1
offset = 0 offset = 0
bytes = 16 bytes = 24
mem { mem {
0x000003ff 0x0000002f 0x000fffff 0x0000000e 0x000003ff 0x0000002f 0x0000001f 0x00000001
0x000fffff 0x0000000e
} }
} }
bincode { bincode {
0xd0800205 0x00400780 0xa0000211 0x04000780 0xd0800205 0x00400780 0xa0000209 0x04000780
0xa0000019 0x04000780 0x30040801 0xc4100780 0xa0000019 0x04000780 0x30040401 0xc4100780
0x20000c25 0x04000780 0x308113fd 0x644107c8 0x20000c11 0x04000780 0x308109fd 0x644107c8
0xa0011003 0x00000000 0x3002121d 0xc4100780 0xa0011003 0x00000000 0x3002081d 0xc4100780
0x10011003 0x00000280 0xa0004e01 0x04200780 0x10011003 0x00000280 0xa0004e01 0x04200780
0x30070005 0xc4100780 0x30060001 0xc4100780 0x30070005 0xc4100780 0x30060001 0xc4100780
0x20008200 0x2100ec00 0x20000e01 0x04000780 0x20008200 0x2100ee00 0x20000e01 0x04000780
0xd00e0001 0x80c00780 0x00000e05 0xc0000780 0xd00e0001 0x80c00780 0x00000e05 0xc0000780
0x04041401 0xe4200780 0xf0000001 0xe0000002 0x04025601 0xe4200780 0xf0000001 0xe0000002
0x861ffe03 0x00000000 0xa0004c09 0x04200780 0x861ffe03 0x00000000 0xa0004c05 0x04200780
0x1100f004 0x1100f200 0x40040214 0x4003082c 0x1000d201 0x0423c780 0x4002020d 0x00000780
0x10018029 0x00000003 0x1000ce0d 0x0423c780 0x3010060d 0xc4100780 0x6002000d 0x0000c780
0x30100a21 0xc4100780 0x30101615 0xc4100780 0x1000d401 0x0423c780 0x40010c15 0x00000780
0x3003140d 0xc4000780 0x60040021 0x00020780 0x60000e15 0x00014780 0x30100a15 0xc4100780
0x60020815 0x00014780 0x3003900c 0x1100f004 0x60000c01 0x00014780 0x308209fd 0x6c4107c8
0x400a0229 0x00000780 0x3003d20d 0xa4200780 0xa0033003 0x00000000 0x20000015 0x04010780
0x600b0029 0x00028780 0x40030c2d 0x00000780 0x10033003 0x00000280 0xd0095805 0x20000780
0x30101429 0xc4100780 0x60020e2d 0x0002c780 0x2400c001 0x04210780 0x30000a01 0xac000780
0x600a0001 0x00028780 0xd0105005 0x20000780 0x308201fd 0x6c40c7c8 0xa0031003 0x00000000
0x30101615 0xc4100780 0x20000001 0x04024780 0x10030003 0x00000280 0xd0096005 0x20000780
0x60020c05 0x00014780 0x3400c1fd 0x6c20c7c8 0x2400c001 0x04214780 0x30020001 0xc4100780
0x300113fd 0x6c0042c8 0xd010a005 0x20000780 0x2000cc01 0x04200780 0x20008001 0x0ffffffb
0x2400c001 0x04200680 0x30020001 0xc4100680 0xd00e000d 0x80c00780 0x1400d401 0x0423c780
0x2000ca01 0x04200680 0xd00e0001 0x80c00680 0x30000601 0xec000780 0x10031003 0x00000780
0x1000f801 0x0403c100 0x301f0005 0xec100780 0x1000f801 0x0403c780 0x00000e05 0xc0000782
0x30010001 0xc4100780 0xd0000201 0x04008780 0x04001601 0xe4200780 0x1000d401 0x0423c782
0x00000e05 0xc0000780 0x30820001 0xac400780 0x4003000d 0x00000780 0x60020225 0x0000c780
0x04001401 0xe4200780 0x861ffe03 0x00000000 0x10018021 0x00000003 0x1000d00d 0x0423c780
0x307cd1fd 0x6c20c7c8 0x1000f815 0x0403c780 0x30101225 0xc4100780 0x3003100d 0xc4000780
0x1004a003 0x00000280 0x1000d001 0x0423c780 0x60020021 0x00024780 0x3003900c 0x1100f200
0x40090005 0x00000780 0x60080205 0x00004780 0x3003d40d 0xa4200780 0x40010c25 0x00000780
0x30100205 0xc4100780 0x60080001 0x00004780 0x60000e25 0x00024780 0x30101225 0xc4100780
0x200a8005 0x00000003 0x00020205 0xc0000780 0x60000c01 0x00024780 0x30040001 0x6c0107d0
0xa0049003 0x00000000 0x2000d005 0x04200780 0xa00001fd 0x0c0147c8 0xa004e003 0x00000000
0x20018001 0x00000003 0x3606c225 0xec200780 0x1004d003 0x00001100 0xd0096005 0x20000780
0x300101fd 0x6c0147c8 0x20000a15 0x04024780 0x2400c001 0x04214780 0x30020001 0xc4100780
0x10044003 0x00000280 0xf0000001 0xe0000002 0x2000cc01 0x04200780 0xd00e0025 0x80c00780
0x200005fd 0x040107c8 0xa005d003 0x00000000 0x1400d401 0x0423c780 0x30001201 0xec000780
0x20018c05 0x00000003 0x10057003 0x00000280 0x1004e003 0x00000780 0x1000f801 0x0403c780
0xd0105005 0x20000780 0x1400c001 0x0423c780 0x00000e05 0xc0000782 0x04005601 0xe4200780
0x2040d001 0x04200780 0x40010409 0x00000780 0x861ffe03 0x00000000 0xd0095805 0x20000780
0x60000609 0x00008780 0x30100409 0xc4100780 0x3500e029 0x00000003 0x307c15fd 0x6c0187d8
0x60000401 0x00008780 0x20000001 0x04014780 0x1000f825 0x0403c780 0x1400c001 0x0423c780
0x1005d003 0x00000780 0x1000d001 0x0423c780 0x10068003 0x00001280 0x20001401 0x04010780
0x40010409 0x00000780 0x60000609 0x00008780 0x200b8001 0x00000003 0x102c8011 0x00000003
0x30100409 0xc4100780 0x60000401 0x00008780 0x00020009 0xc0000780 0x00000805 0xc0000780
0x20000001 0x04014780 0x00000e05 0xc0000782 0x1000f811 0x0403c780 0xd4098011 0x20000780
0x04021401 0xe4200780 0x861ffe03 0x00000000 0xd801000d 0x20000780 0x20018811 0x00000003
0x300607fd 0x640107c8 0x308309fd 0x6440c2c8 0x1000c001 0x0423c784 0xd0095811 0x20000780
0x30000003 0x00000100 0x2101ee05 0x00000003 0x6c00c025 0x80224780 0x3004c1fd 0x6c2147dc
0x100f8001 0x00000003 0x30010001 0xc4000780 0xd8000809 0x20000780 0xd4000805 0x20000780
0x40014e09 0x00200780 0x30100409 0xc4100780 0x1000c001 0x0423c784 0x1005d003 0x00001280
0x60004e09 0x00208780 0x30040c0d 0xc4100780 0xd0096809 0x20000780 0x30050029 0x6c00c780
0x30010805 0xc4000780 0x20069000 0x2003880c 0x1000f811 0x0403c780 0x00000e05 0xc0000780
0x20000405 0x04004780 0x00020605 0xc0000780 0x1800c001 0x0423c780 0xa0001429 0x2c014780
0x20000001 0x04004780 0xd4085005 0x20000780 0x10000611 0x2440c280 0x30001201 0xec000780
0x30020005 0xc4100780 0x1500e000 0x2101e804 0xd4015805 0x20000780 0xd00a09fd 0x040007c8
0x2440c025 0x04200780 0xd009a805 0x20000780
0x2400c001 0x04214680 0x30020001 0xc4100680
0x2000ca01 0x04200680 0xd00e0025 0xa0c00680
0x1000f825 0x0403c100 0x861ffe03 0x00000000
0x301f1211 0xec100780 0x30011201 0xc4100780
0xd0000801 0x04008780 0x00000e05 0xc0000780
0x30840001 0xac400780 0x04001601 0xe4200780
0x861ffe03 0x00000000 0xd0095805 0x20000780
0x1000d215 0x0423c780 0x20018c11 0x00000003
0x1000d201 0x0423c780 0x3505e014 0x40011024
0x60001225 0x00024780 0x400b1029 0x00000780
0x30101225 0xc4100780 0x600a1229 0x00028780
0x200003fd 0x040087c8 0x60001025 0x00024780
0x30101401 0xc4100780 0x307cd3fd 0x6c20c7d8
0x600a1025 0x00000100 0x1009f003 0x00001280
0x1000d201 0x0423c780 0x40050005 0x00000780
0x60040205 0x00004780 0x30100205 0xc4100780
0x60040011 0x00004780 0x200b8801 0x00000003
0x00020005 0xc0000780 0xa009e003 0x00000000
0x2000d205 0x04210780 0x20018811 0x00000003
0x3606c201 0xec200780 0x300109fd 0x6c0147c8
0x20001225 0x04000780 0x10099003 0x00000280
0xf0000001 0xe0000002 0x861ffe03 0x00000000
0x00000e05 0xc0000780 0x04001601 0xe4224780
0x861ffe03 0x00000000 0x300607fd 0x640107c8
0x308505fd 0x6440c2c8 0x30000003 0x00000100
0x2101f00d 0x00000003 0x100f8001 0x00000003
0x30030005 0xc4000780 0x40034e01 0x00200780
0x30100001 0xc4100780 0x60024e05 0x00200780
0x3003040d 0xc4000780 0x20001011 0x04018780
0x30040c01 0xc4100780 0x20038204 0x20008400
0x20000805 0x04004780 0x00020005 0xc0000780
0x30020205 0xc4100780 0x1500f600 0x2101e804
0xd00e0201 0xa0c00781 0xd00e0201 0xa0c00781
} }
} }
@@ -1515,7 +1549,7 @@ code {
code { code {
name = cudaCalcLargePartition name = cudaCalcLargePartition
lmem = 0 lmem = 0
smem = 2280 smem = 2284
reg = 10 reg = 10
bar = 1 bar = 1
const { const {
@@ -1535,28 +1569,28 @@ code {
0xa0011003 0x00000000 0x30020411 0xc4100780 0xa0011003 0x00000000 0x30020411 0xc4100780
0x10011003 0x00000280 0xa0004e05 0x04200780 0x10011003 0x00000280 0xa0004e05 0x04200780
0x30070215 0xc4100780 0x30060205 0xc4100780 0x30070215 0xc4100780 0x30060205 0xc4100780
0x20018a04 0x2101ec04 0x20000805 0x04004780 0x20018a04 0x2101ee04 0x20000805 0x04004780
0xd00e0205 0x80c00780 0x00000805 0xc0000780 0xd00e0205 0x80c00780 0x00000805 0xc0000780
0x04041401 0xe4204780 0xf0000001 0xe0000002 0x04041601 0xe4204780 0xf0000001 0xe0000002
0x861ffe03 0x00000000 0x307cd1fd 0x6c20c7c8 0x861ffe03 0x00000000 0x307cd3fd 0x6c20c7c8
0x1000f819 0x0403c780 0x10046003 0x00000280 0x1000f819 0x0403c780 0x10046003 0x00000280
0xa0004c15 0x04200780 0x1000d005 0x0423c780 0xa0004c15 0x04200780 0x1000d205 0x0423c780
0x400a061d 0x00000780 0x30100e1d 0xc4100780 0x400a061d 0x00000780 0x30100e1d 0xc4100780
0x600a0405 0x0001c780 0x3082d015 0xac600780 0x600a0405 0x0001c780 0x3082d215 0xac600780
0x2000d021 0x04204780 0xa0045003 0x00000000 0x2000d221 0x04204780 0xa0045003 0x00000000
0x30000bfd 0x6c0107c8 0x2001841c 0x20088420 0x30000bfd 0x6c0107c8 0x2001841c 0x20088420
0x10000405 0x0403c780 0xd0105005 0x20000780 0x10000405 0x0403c780 0xd0105805 0x20000780
0x3407c1fd 0x6c20c7d8 0x3001d1fd 0x6c2112d8 0x3407c1fd 0x6c20c7d8 0x3001d3fd 0x6c2112d8
0xa002d003 0x00000000 0x1002c003 0x00001100 0xa002d003 0x00000000 0x1002c003 0x00001100
0xd010a005 0x20000780 0x2400c009 0x0421c780 0xd010a805 0x20000780 0x2400c009 0x0421c780
0x30020409 0xc4100780 0x2000ca09 0x04208780 0x30020409 0xc4100780 0x2000ca09 0x04208780
0xd00e0425 0x80c00780 0x1002d003 0x00000780 0xd00e0425 0x80c00780 0x1002d003 0x00000780
0x1000f825 0x0403c780 0x301f1209 0xec100782 0x1000f825 0x0403c780 0x301f1209 0xec100782
0x30011225 0xc4100780 0xd0090409 0x04008780 0x30011225 0xc4100780 0xd0090409 0x04008780
0x00000805 0xc0000780 0x30830409 0xac400780 0x00000805 0xc0000780 0x30830409 0xac400780
0x04001401 0xe4208780 0x861ffe03 0x00000000 0x04001601 0xe4208780 0x861ffe03 0x00000000
0xa003f003 0x00000000 0x10000009 0x0403c780 0xa003f003 0x00000000 0x10000009 0x0403c780
0x1003f003 0x00000100 0x200a8025 0x00000003 0x1003f003 0x00000100 0x200b8025 0x00000003
0x00021205 0xc0000780 0x20108409 0x00000003 0x00021205 0xc0000780 0x20108409 0x00000003
0x3403c025 0xec200780 0x30020bfd 0x6c0107d8 0x3403c025 0xec200780 0x30020bfd 0x6c0107d8
0x20000c19 0x04024780 0xd4008005 0x20000780 0x20000c19 0x04024780 0xd4008005 0x20000780
@@ -1565,24 +1599,24 @@ code {
0x30080ffd 0x6c0047d8 0x20008205 0x00000013 0x30080ffd 0x6c0047d8 0x20008205 0x00000013
0x10021003 0x00001280 0xf0000001 0xe0000002 0x10021003 0x00001280 0xf0000001 0xe0000002
0x30830c05 0xac400780 0x00000805 0xc0000780 0x30830c05 0xac400780 0x00000805 0xc0000780
0x04021401 0xe4204780 0xd4085009 0x20000780 0x04021601 0xe4204780 0xd4085809 0x20000780
0x1900f004 0x2901e004 0x04021401 0xe4204780 0x1900f004 0x2901e004 0x04021601 0xe4204780
0x1900e804 0x2901e004 0x04021401 0xe4204780 0x1900e804 0x2901e004 0x04021601 0xe4204780
0x1900e404 0x2901e004 0x04021401 0xe4204780 0x1900e404 0x2901e004 0x04021601 0xe4204780
0x1800c205 0x0423c780 0x307c01fd 0x640087c8 0x1800c205 0x0423c780 0x307c01fd 0x640087c8
0x2800c001 0x04204780 0x308407fd 0x6440c2c8 0x2800c001 0x04204780 0x308407fd 0x6440c2c8
0x04021401 0xe4200780 0x30000003 0x00000100 0x04021601 0xe4200780 0x30000003 0x00000100
0xd0105005 0x20000780 0x2101ee19 0x00000003 0xd0105805 0x20000780 0x2101f019 0x00000003
0x100f8005 0x00000003 0x20018609 0x00000003 0x100f8005 0x00000003 0x20018609 0x00000003
0x1000d001 0x0423c780 0x30060205 0xc4000780 0x1000d201 0x0423c780 0x30060205 0xc4000780
0x1100f014 0x41032e1c 0x40000a24 0x3505e014 0x1100f214 0x41032e1c 0x40000a24 0x3505e014
0x30100e21 0xc4100780 0x6001081d 0x00024780 0x30100e21 0xc4100780 0x6001081d 0x00024780
0x3006060d 0xc4000780 0x400b0819 0x00000780 0x3006060d 0xc4000780 0x400b0819 0x00000780
0x60024e05 0x00220780 0x00000805 0xc0000780 0x60024e05 0x00220780 0x00000805 0xc0000780
0x30100e1d 0xc4100780 0x600a0a11 0x00018780 0x30100e1d 0xc4100780 0x600a0a11 0x00018780
0x2000020d 0x0400c780 0xa0004c05 0x042007c0 0x2000020d 0x0400c780 0xa0004c05 0x042007c0
0x60000801 0x0001c780 0x30100811 0xc4100780 0x60000801 0x0001c780 0x30100811 0xc4100780
0xd4085005 0x20000780 0x20000205 0x0400c780 0xd4085805 0x20000780 0x20000205 0x0400c780
0x600a0801 0x00010100 0x3483c009 0xac600780 0x600a0801 0x00010100 0x3483c009 0xac600780
0x30020205 0xc4100780 0x20028000 0x2101e804 0x30020205 0xc4100780 0x20028000 0x2101e804
0xd00e0201 0xa0c00781 0xd00e0201 0xa0c00781