diff --git a/CUETools.Codecs.FLACCL/CUETools.Codecs.FLACCL.csproj b/CUETools.Codecs.FLACCL/CUETools.Codecs.FLACCL.csproj
index 1282a58..8e31c17 100644
--- a/CUETools.Codecs.FLACCL/CUETools.Codecs.FLACCL.csproj
+++ b/CUETools.Codecs.FLACCL/CUETools.Codecs.FLACCL.csproj
@@ -35,10 +35,6 @@
true
-
- False
- OpenCLNet.dll
-
@@ -53,6 +49,10 @@
+
+ {758285C6-1ACA-458A-9906-EE6701D5AF87}
+ OpenCLNet
+
{082D6B9E-326E-4D15-9798-EDAE9EDE70A6}
CUETools.Codecs.FLAKE
@@ -67,8 +67,9 @@
-
-
+
+ PreserveNewest
+
ResXFileCodeGenerator
Resources.Designer.cs
@@ -86,6 +87,7 @@
-
+
+
\ No newline at end of file
diff --git a/CUETools.Codecs.FLACCL/FLACCLWriter.cs b/CUETools.Codecs.FLACCL/FLACCLWriter.cs
index bbd537b..d0ce084 100644
--- a/CUETools.Codecs.FLACCL/FLACCLWriter.cs
+++ b/CUETools.Codecs.FLACCL/FLACCLWriter.cs
@@ -1221,7 +1221,7 @@ namespace CUETools.Codecs.FLACCL
//task.openCLCQ.EnqueueReadBuffer(task.cudaLPCData, true, 0, sizeof(float) * 1024, (IntPtr)lpcs);
task.openCLCQ.EnqueueBarrier();
- task.openCLCQ.EnqueueNDRangeKernel(task.cudaQuantizeLPC, 2, null, new int[] { task.nAutocorTasksPerChannel * 32, channelsCount * task.frameCount * 4 }, new int[] { 32, 4 });
+ task.openCLCQ.EnqueueNDRangeKernel(task.cudaQuantizeLPC, 2, null, new int[] { task.nAutocorTasksPerChannel * 32, channelsCount * task.frameCount }, new int[] { 32, 1 });
//cuda.SetFunctionBlockShape(task.cudaQuantizeLPC, 32, 4, 1);
task.openCLCQ.EnqueueBarrier();
@@ -1518,7 +1518,7 @@ namespace CUETools.Codecs.FLACCL
OCLMan = new OpenCLManager();
// Attempt to save binaries after compilation, as well as load precompiled binaries
// to avoid compilation. Usually you'll want this to be true.
- OCLMan.AttemptUseBinaries = false; // true;
+ OCLMan.AttemptUseBinaries = true; // true;
// Attempt to compile sources. This should probably be true for almost all projects.
// Setting it to false means that when you attempt to compile "mysource.cl", it will
// only scan the precompiled binary directory for a binary corresponding to a source
@@ -1539,32 +1539,33 @@ namespace CUETools.Codecs.FLACCL
"#define GROUP_SIZE " + groupSize.ToString() + "\n";
// The BuildOptions string is passed directly to clBuild and can be used to do debug builds etc
OCLMan.BuildOptions = "";
-
+ OCLMan.SourcePath = System.IO.Path.GetDirectoryName(GetType().Assembly.Location);
+ //OCLMan.BinaryPath = ;
OCLMan.CreateDefaultContext(0, DeviceType.GPU);
openCLContext = OCLMan.Context;
- //try
- //{
- // openCLProgram = OCLMan.CompileFile("flac.cl");
- //}
- //catch (OpenCLBuildException ex)
- //{
- // string buildLog = ex.BuildLogs[0];
- // throw ex;
- //}
- using (Stream kernel = GetType().Assembly.GetManifestResourceStream(GetType(), "flac.cl"))
- using (StreamReader sr = new StreamReader(kernel))
+ try
{
- try
- {
- openCLProgram = OCLMan.CompileSource(sr.ReadToEnd()); ;
- }
- catch (OpenCLBuildException ex)
- {
- string buildLog = ex.BuildLogs[0];
- throw ex;
- }
+ openCLProgram = OCLMan.CompileFile("flac.cl");
}
+ catch (OpenCLBuildException ex)
+ {
+ string buildLog = ex.BuildLogs[0];
+ throw ex;
+ }
+ //using (Stream kernel = GetType().Assembly.GetManifestResourceStream(GetType(), "flac.cl"))
+ //using (StreamReader sr = new StreamReader(kernel))
+ //{
+ // try
+ // {
+ // openCLProgram = OCLMan.CompileSource(sr.ReadToEnd()); ;
+ // }
+ // catch (OpenCLBuildException ex)
+ // {
+ // string buildLog = ex.BuildLogs[0];
+ // throw ex;
+ // }
+ //}
#if TTTTKJHSKJH
var openCLPlatform = OpenCL.GetPlatform(0);
openCLContext = openCLPlatform.CreateDefaultContext();
@@ -2427,9 +2428,7 @@ namespace CUETools.Codecs.FLACCL
cudaChooseBestMethod.SetArg(1, cudaResidualOutput);
cudaChooseBestMethod.SetArg(2, (uint)nResidualTasksPerChannel);
- int threadsY = 4;
-
- openCLCQ.EnqueueNDRangeKernel(cudaChooseBestMethod, 2, null, new int[] { 32, channelsCount * frameCount * threadsY }, new int[] { 32, threadsY });
+ openCLCQ.EnqueueNDRangeKernel(cudaChooseBestMethod, 2, null, new int[] { 32, channelsCount * frameCount }, new int[] { 32, 1 });
//cuda.SetFunctionBlockShape(task.cudaChooseBestMethod, 32, 8, 1);
}
diff --git a/CUETools.Codecs.FLACCL/flac.cl b/CUETools.Codecs.FLACCL/flac.cl
index 47257c5..0ad9887 100644
--- a/CUETools.Codecs.FLACCL/flac.cl
+++ b/CUETools.Codecs.FLACCL/flac.cl
@@ -279,7 +279,7 @@ void cudaComputeLPC(
lpcs[shared.lpcOffs + MAX_ORDER * 32 + get_local_id(0)] = shared.error[get_local_id(0)];
}
-__kernel __attribute__((reqd_work_group_size(32, 4, 1)))
+__kernel __attribute__((reqd_work_group_size(32, 1, 1)))
void cudaQuantizeLPC(
__global FLACCLSubframeTask *tasks,
__global float*lpcs,
@@ -291,13 +291,13 @@ void cudaQuantizeLPC(
{
__local struct {
FLACCLSubframeData task;
- volatile int tmpi[128];
+ volatile int tmpi[32];
volatile int index[64];
volatile float error[64];
volatile int lpcOffs;
} shared;
- const int tid = get_local_id(0) + get_local_id(1) * 32;
+ const int tid = get_local_id(0);
// fetch task data
if (tid < sizeof(shared.task) / sizeof(int))
@@ -307,18 +307,15 @@ void cudaQuantizeLPC(
barrier(CLK_LOCAL_MEM_FENCE);
// Select best orders based on Akaike's Criteria
- if (get_local_id(1) == 0)
- {
- shared.index[tid] = min(MAX_ORDER - 1, tid);
- shared.error[tid] = shared.task.blocksize * 64 + tid;
- shared.index[32 + tid] = min(MAX_ORDER - 1, tid);
- shared.error[32 + tid] = shared.task.blocksize * 64 + tid;
+ shared.index[tid] = min(MAX_ORDER - 1, tid);
+ shared.error[tid] = shared.task.blocksize * 64 + tid;
+ shared.index[32 + tid] = min(MAX_ORDER - 1, tid);
+ shared.error[32 + tid] = shared.task.blocksize * 64 + tid;
- // Load prediction error estimates
- if (tid < MAX_ORDER)
- shared.error[tid] = shared.task.blocksize * log(lpcs[shared.lpcOffs + MAX_ORDER * 32 + tid]) + tid * 5.12f * log(shared.task.blocksize);
- //shared.error[get_local_id(0)] = shared.task.blocksize * log(lpcs[shared.lpcOffs + MAX_ORDER * 32 + get_local_id(0)]) + get_local_id(0) * 0.30f * (shared.task.abits + 1) * log(shared.task.blocksize);
- }
+ // Load prediction error estimates
+ if (tid < MAX_ORDER)
+ shared.error[tid] = shared.task.blocksize * log(lpcs[shared.lpcOffs + MAX_ORDER * 32 + tid]) + tid * 5.12f * log(shared.task.blocksize);
+ //shared.error[get_local_id(0)] = shared.task.blocksize * log(lpcs[shared.lpcOffs + MAX_ORDER * 32 + get_local_id(0)]) + get_local_id(0) * 0.30f * (shared.task.abits + 1) * log(shared.task.blocksize);
barrier(CLK_LOCAL_MEM_FENCE);
// Sort using bitonic sort
@@ -327,17 +324,12 @@ void cudaQuantizeLPC(
int ddd = (tid & (size / 2)) == 0;
for(int stride = size / 2; stride > 0; stride >>= 1){
int pos = 2 * tid - (tid & (stride - 1));
- float e0, e1;
- int i0, i1;
- if (get_local_id(1) == 0)
- {
- e0 = shared.error[pos];
- e1 = shared.error[pos + stride];
- i0 = shared.index[pos];
- i1 = shared.index[pos + stride];
- }
+ float e0 = shared.error[pos];
+ float e1 = shared.error[pos + stride];
+ int i0 = shared.index[pos];
+ int i1 = shared.index[pos + stride];
barrier(CLK_LOCAL_MEM_FENCE);
- if (get_local_id(1) == 0 && (e0 >= e1) == ddd)
+ if ((e0 >= e1) == ddd)
{
shared.error[pos] = e1;
shared.error[pos + stride] = e0;
@@ -353,17 +345,12 @@ void cudaQuantizeLPC(
for(int stride = 32; stride > 0; stride >>= 1){
//barrier(CLK_LOCAL_MEM_FENCE);
int pos = 2 * tid - (tid & (stride - 1));
- float e0, e1;
- int i0, i1;
- if (get_local_id(1) == 0)
- {
- e0 = shared.error[pos];
- e1 = shared.error[pos + stride];
- i0 = shared.index[pos];
- i1 = shared.index[pos + stride];
- }
+ float e0 = shared.error[pos];
+ float e1 = shared.error[pos + stride];
+ int i0 = shared.index[pos];
+ int i1 = shared.index[pos + stride];
barrier(CLK_LOCAL_MEM_FENCE);
- if (get_local_id(1) == 0 && e0 >= e1)
+ if (e0 >= e1)
{
shared.error[pos] = e1;
shared.error[pos + stride] = e0;
@@ -375,11 +362,10 @@ void cudaQuantizeLPC(
}
// Quantization
- for (int ii = 0; ii < taskCountLPC; ii += get_local_size(1))
+ for (int i = 0; i < taskCountLPC; i ++)
{
- int i = ii + get_local_id(1);
int order = shared.index[i >> precisions];
- float lpc = get_local_id(0) <= order ? lpcs[shared.lpcOffs + order * 32 + get_local_id(0)] : 0.0f;
+ float lpc = tid <= order ? lpcs[shared.lpcOffs + order * 32 + tid] : 0.0f;
// get 15 bits of each coeff
int coef = convert_int_rte(lpc * (1 << 15));
// remove sign bits
@@ -388,7 +374,7 @@ void cudaQuantizeLPC(
// OR reduction
for (int l = get_local_size(0) / 2; l > 1; l >>= 1)
{
- if (get_local_id(0) < l)
+ if (tid < l)
shared.tmpi[tid] |= shared.tmpi[tid + l];
barrier(CLK_LOCAL_MEM_FENCE);
}
@@ -397,44 +383,44 @@ void cudaQuantizeLPC(
//int cbits = max(3, min(10, 5 + (shared.task.abits >> 1))); // - convert_int_rte(shared.PE[order - 1])
int cbits = max(3, min(min(13 - minprecision + (i - ((i >> precisions) << precisions)) - (shared.task.blocksize <= 2304) - (shared.task.blocksize <= 1152) - (shared.task.blocksize <= 576), shared.task.abits), clz(order) + 1 - shared.task.abits));
// calculate shift based on precision and number of leading zeroes in coeffs
- int shift = max(0,min(15, clz(shared.tmpi[get_local_id(1) * 32] | shared.tmpi[get_local_id(1) * 32 + 1]) - 18 + cbits));
+ int shift = max(0,min(15, clz(shared.tmpi[0] | shared.tmpi[1]) - 18 + cbits));
//cbits = 13;
//shift = 15;
//if (shared.task.abits + 32 - clz(order) < shift
- //int shift = max(0,min(15, (shared.task.abits >> 2) - 14 + clz(shared.tmpi[get_local_id(0) & ~31]) + ((32 - clz(order))>>1)));
+ //int shift = max(0,min(15, (shared.task.abits >> 2) - 14 + clz(shared.tmpi[tid & ~31]) + ((32 - clz(order))>>1)));
// quantize coeffs with given shift
coef = convert_int_rte(clamp(lpc * (1 << shift), -1 << (cbits - 1), 1 << (cbits - 1)));
// error correction
- //shared.tmp[get_local_id(0)] = (get_local_id(0) != 0) * (shared.arp[get_local_id(0) - 1]*(1 << shared.task.shift) - shared.task.coefs[get_local_id(0) - 1]);
- //shared.task.coefs[get_local_id(0)] = max(-(1 << (shared.task.cbits - 1)), min((1 << (shared.task.cbits - 1))-1, convert_int_rte((shared.arp[get_local_id(0)]) * (1 << shared.task.shift) + shared.tmp[get_local_id(0)])));
+ //shared.tmp[tid] = (tid != 0) * (shared.arp[tid - 1]*(1 << shared.task.shift) - shared.task.coefs[tid - 1]);
+ //shared.task.coefs[tid] = max(-(1 << (shared.task.cbits - 1)), min((1 << (shared.task.cbits - 1))-1, convert_int_rte((shared.arp[tid]) * (1 << shared.task.shift) + shared.tmp[tid])));
// remove sign bits
shared.tmpi[tid] = coef ^ (coef >> 31);
barrier(CLK_LOCAL_MEM_FENCE);
// OR reduction
for (int l = get_local_size(0) / 2; l > 1; l >>= 1)
{
- if (get_local_id(0) < l)
+ if (tid < l)
shared.tmpi[tid] |= shared.tmpi[tid + l];
barrier(CLK_LOCAL_MEM_FENCE);
}
//SUM32(shared.tmpi,tid,|=);
// calculate actual number of bits (+1 for sign)
- cbits = 1 + 32 - clz(shared.tmpi[get_local_id(1) * 32] | shared.tmpi[get_local_id(1) * 32 + 1]);
+ cbits = 1 + 32 - clz(shared.tmpi[0] | shared.tmpi[1]);
// output shift, cbits and output coeffs
if (i < taskCountLPC)
{
int taskNo = get_group_id(1) * taskCount + get_group_id(0) * taskCountLPC + i;
- if (get_local_id(0) == 0)
+ if (tid == 0)
tasks[taskNo].data.shift = shift;
- if (get_local_id(0) == 0)
+ if (tid == 0)
tasks[taskNo].data.cbits = cbits;
- if (get_local_id(0) == 0)
+ if (tid == 0)
tasks[taskNo].data.residualOrder = order + 1;
- if (get_local_id(0) <= order)
- tasks[taskNo].coefs[get_local_id(0)] = coef;
+ if (tid <= order)
+ tasks[taskNo].coefs[tid] = coef;
}
}
}
@@ -519,62 +505,63 @@ void cudaEstimateResidual(
output[get_group_id(0)] = residual[0];
}
-__kernel void cudaChooseBestMethod(
+__kernel __attribute__((reqd_work_group_size(32, 1, 1)))
+void cudaChooseBestMethod(
__global FLACCLSubframeTask *tasks,
__global int *residual,
int taskCount
)
{
__local struct {
- volatile int index[128];
- volatile int length[256];
- volatile FLACCLSubframeTask task[8];
+ volatile int index[32];
+ volatile int length[32];
} shared;
- const int tid = get_local_id(0) + get_local_id(1) * 32;
+ __local FLACCLSubframeData task;
+ const int tid = get_local_id(0);
shared.length[tid] = 0x7fffffff;
shared.index[tid] = tid;
- for (int task = 0; task < taskCount; task += get_local_size(1))
- if (task + get_local_id(1) < taskCount)
+ for (int taskNo = 0; taskNo < taskCount; taskNo++)
+ {
+ // fetch task data
+ if (tid < sizeof(task) / sizeof(int))
+ ((__local int*)&task)[tid] = ((__global int*)(&tasks[taskNo + taskCount * get_group_id(1)].data))[tid];
+
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ if (tid == 0)
{
- // fetch task data
- ((__local int*)&shared.task[get_local_id(1)])[get_local_id(0)] =
- ((__global int*)(tasks + task + get_local_id(1) + taskCount * get_group_id(1)))[get_local_id(0)];
+ // fetch part sum
+ int partLen = residual[taskNo + taskCount * get_group_id(1)];
+ //// 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);
+ //// calculate rice parameter
+ //int k = max(0, min(14, convert_int_rtz(log2((psum + 0.000001f) / (residualLen + 0.000001f) + 0.5f))));
+ //// calculate part bit length
+ //int partLen = residualLen * (k + 1) + (psum >> k);
- barrier(CLK_LOCAL_MEM_FENCE);
-
- if (get_local_id(0) == 0)
- {
- // fetch part sum
- int partLen = residual[task + get_local_id(1) + taskCount * get_group_id(1)];
- //// calculate part size
- //int residualLen = shared.task[get_local_id(1)].data.blocksize - shared.task[get_local_id(1)].data.residualOrder;
- //residualLen = residualLen * (shared.task[get_local_id(1)].data.type != Constant || psum != 0);
- //// calculate rice parameter
- //int k = max(0, min(14, convert_int_rtz(log2((psum + 0.000001f) / (residualLen + 0.000001f) + 0.5f))));
- //// calculate part bit length
- //int partLen = residualLen * (k + 1) + (psum >> k);
-
- int obits = shared.task[get_local_id(1)].data.obits - shared.task[get_local_id(1)].data.wbits;
- shared.length[task + get_local_id(1)] =
- min(obits * shared.task[get_local_id(1)].data.blocksize,
- shared.task[get_local_id(1)].data.type == Fixed ? shared.task[get_local_id(1)].data.residualOrder * obits + 6 + (4 * 1/2) + partLen :
- shared.task[get_local_id(1)].data.type == LPC ? shared.task[get_local_id(1)].data.residualOrder * obits + 4 + 5 + shared.task[get_local_id(1)].data.residualOrder * shared.task[get_local_id(1)].data.cbits + 6 + (4 * 1/2)/* << porder */ + partLen :
- shared.task[get_local_id(1)].data.type == Constant ? obits * (1 + shared.task[get_local_id(1)].data.blocksize * (partLen != 0)) :
- obits * shared.task[get_local_id(1)].data.blocksize);
- }
+ int obits = task.obits - task.wbits;
+ shared.length[taskNo] =
+ min(obits * task.blocksize,
+ task.type == Fixed ? task.residualOrder * obits + 6 + (4 * 1/2) + partLen :
+ task.type == LPC ? task.residualOrder * obits + 4 + 5 + task.residualOrder * task.cbits + 6 + (4 * 1/2)/* << porder */ + partLen :
+ task.type == Constant ? obits * (1 + task.blocksize * (partLen != 0)) :
+ obits * task.blocksize);
}
+
+ 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;
- barrier(CLK_LOCAL_MEM_FENCE);
if (tid < taskCount)
tasks[tid + taskCount * get_group_id(1)].data.size = shared.length[tid];
int l1 = shared.length[tid];
- for (int sh = 8; sh > 0; sh --)
+ for (int sh = 4; sh > 0; sh --)
{
- if (tid + (1 << sh) < get_local_size(0) * get_local_size(1))
+ if (tid < (1 << sh))
{
int l2 = shared.length[tid + (1 << sh)];
shared.index[tid] = shared.index[tid + ((l2 < l1) << sh)];
@@ -586,7 +573,8 @@ __kernel void cudaChooseBestMethod(
tasks[taskCount * get_group_id(1)].data.best_index = taskCount * get_group_id(1) + shared.index[shared.length[1] < shared.length[0]];
}
-__kernel void cudaCopyBestMethod(
+__kernel __attribute__((reqd_work_group_size(64, 1, 1)))
+void cudaCopyBestMethod(
__global FLACCLSubframeTask *tasks_out,
__global FLACCLSubframeTask *tasks,
int count
@@ -600,7 +588,8 @@ __kernel void cudaCopyBestMethod(
((__global int*)(tasks_out + get_group_id(1)))[get_local_id(0)] = ((__global int*)(tasks + best_index))[get_local_id(0)];
}
-__kernel void cudaCopyBestMethodStereo(
+__kernel __attribute__((reqd_work_group_size(64, 1, 1)))
+void cudaCopyBestMethodStereo(
__global FLACCLSubframeTask *tasks_out,
__global FLACCLSubframeTask *tasks,
int count
@@ -652,233 +641,95 @@ __kernel void cudaCopyBestMethodStereo(
tasks_out[2 * get_group_id(1) + 1].data.residualOffs = tasks[shared.best_index[1]].data.residualOffs;
}
-//__kernel void cudaEncodeResidual(
-// int*output,
-// int*samples,
-// FLACCLSubframeTask *tasks
-// )
-//{
-// __local struct {
-// int data[256 + 32];
-// FLACCLSubframeTask task;
-// } shared;
-// const int tid = get_local_id(0);
-// if (get_local_id(0) < sizeof(shared.task) / sizeof(int))
-// ((int*)&shared.task)[get_local_id(0)] = ((int*)(&tasks[get_group_id(1)]))[get_local_id(0)];
-// barrier(CLK_LOCAL_MEM_FENCE);
-// const int partSize = get_local_size(0);
-// const int pos = get_group_id(0) * partSize;
-// const int dataLen = min(shared.task.data.blocksize - pos, partSize + shared.task.data.residualOrder);
-//
-// // fetch samples
-// shared.data[tid] = tid < dataLen ? samples[shared.task.data.samplesOffs + pos + tid] >> shared.task.data.wbits : 0;
-// if (tid < 32) shared.data[tid + partSize] = tid + partSize < dataLen ? samples[shared.task.data.samplesOffs + pos + tid + partSize] >> shared.task.data.wbits : 0;
-// const int residualLen = max(0,min(shared.task.data.blocksize - pos - shared.task.data.residualOrder, partSize));
-//
-// barrier(CLK_LOCAL_MEM_FENCE);
-// // compute residual
-// int sum = 0;
-// for (int c = 0; c < shared.task.data.residualOrder; c++)
-// sum += __mul24(shared.data[tid + c], shared.task.coefs[c]);
-// barrier(CLK_LOCAL_MEM_FENCE);
-// shared.data[tid + shared.task.data.residualOrder] -= (sum >> shared.task.data.shift);
-// barrier(CLK_LOCAL_MEM_FENCE);
-// if (tid >= shared.task.data.residualOrder && tid < residualLen + shared.task.data.residualOrder)
-// output[shared.task.data.residualOffs + pos + tid] = shared.data[tid];
-// if (tid + 256 < residualLen + shared.task.data.residualOrder)
-// output[shared.task.data.residualOffs + pos + tid + 256] = shared.data[tid + 256];
-//}
-//
-//__kernel void cudaCalcPartition(
-// int* partition_lengths,
-// int* residual,
-// int* samples,
-// FLACCLSubframeTask *tasks,
-// int max_porder, // <= 8
-// int psize, // == (shared.task.data.blocksize >> max_porder), < 256
-// int parts_per_block // == 256 / psize, > 0, <= 16
-// )
-//{
-// __local struct {
-// int data[256+32];
-// FLACCLSubframeTask task;
-// } shared;
-// const int tid = get_local_id(0) + (get_local_id(1) << 4);
-// if (tid < sizeof(shared.task) / sizeof(int))
-// ((int*)&shared.task)[tid] = ((int*)(&tasks[get_group_id(1)]))[tid];
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// const int parts = min(parts_per_block, (1 << max_porder) - get_group_id(0) * parts_per_block);
-// const int offs = get_group_id(0) * psize * parts_per_block + tid;
-//
-// // fetch samples
-// if (tid < 32) shared.data[tid] = min(offs, tid + shared.task.data.residualOrder) >= 32 ? samples[shared.task.data.samplesOffs + offs - 32] >> shared.task.data.wbits : 0;
-// shared.data[32 + tid] = tid < parts * psize ? samples[shared.task.data.samplesOffs + offs] >> shared.task.data.wbits : 0;
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// // compute residual
-// int s = 0;
-// for (int c = -shared.task.data.residualOrder; c < 0; c++)
-// s += __mul24(shared.data[32 + tid + c], shared.task.coefs[shared.task.data.residualOrder + c]);
-// s = shared.data[32 + tid] - (s >> shared.task.data.shift);
-//
-// if (offs >= shared.task.data.residualOrder && tid < parts * psize)
-// residual[shared.task.data.residualOffs + offs] = s;
-// else
-// s = 0;
-//
-// // convert to unsigned
-// s = min(0xfffff, (s << 1) ^ (s >> 31));
-//
-// //barrier(CLK_LOCAL_MEM_FENCE);
-// //shared.data[tid] = s;
-// //barrier(CLK_LOCAL_MEM_FENCE);
-//
-// //shared.data[tid] = (shared.data[tid] & (0x0000ffff << (tid & 16))) | (((shared.data[tid ^ 16] & (0x0000ffff << (tid & 16))) << (~tid & 16)) >> (tid & 16));
-// //shared.data[tid] = (shared.data[tid] & (0x00ff00ff << (tid & 8))) | (((shared.data[tid ^ 8] & (0x00ff00ff << (tid & 8))) << (~tid & 8)) >> (tid & 8));
-// //shared.data[tid] = (shared.data[tid] & (0x0f0f0f0f << (tid & 4))) | (((shared.data[tid ^ 4] & (0x0f0f0f0f << (tid & 4))) << (~tid & 4)) >> (tid & 4));
-// //shared.data[tid] = (shared.data[tid] & (0x33333333 << (tid & 2))) | (((shared.data[tid ^ 2] & (0x33333333 << (tid & 2))) << (~tid & 2)) >> (tid & 2));
-// //shared.data[tid] = (shared.data[tid] & (0x55555555 << (tid & 1))) | (((shared.data[tid ^ 1] & (0x55555555 << (tid & 1))) << (~tid & 1)) >> (tid & 1));
-// //shared.data[tid] = __popc(shared.data[tid]);
-//
-// barrier(CLK_LOCAL_MEM_FENCE);
-// shared.data[tid + (tid / psize)] = s;
-// //shared.data[tid] = s;
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// s = (psize - shared.task.data.residualOrder * (get_local_id(0) + get_group_id(0) == 0)) * (get_local_id(1) + 1);
-// int dpos = __mul24(get_local_id(0), psize + 1);
-// //int dpos = __mul24(get_local_id(0), psize);
-// // calc number of unary bits for part get_local_id(0) with rice paramater get_local_id(1)
-//#pragma unroll 0
-// for (int i = 0; i < psize; i++)
-// s += shared.data[dpos + i] >> get_local_id(1);
-//
-// // output length
-// const int pos = (15 << (max_porder + 1)) * get_group_id(1) + (get_local_id(1) << (max_porder + 1));
-// if (get_local_id(1) <= 14 && get_local_id(0) < parts)
-// partition_lengths[pos + get_group_id(0) * parts_per_block + get_local_id(0)] = s;
-//}
-//
-//__kernel void cudaCalcPartition16(
-// int* partition_lengths,
-// int* residual,
-// int* samples,
-// FLACCLSubframeTask *tasks,
-// int max_porder, // <= 8
-// int psize, // == 16
-// int parts_per_block // == 16
-// )
-//{
-// __local struct {
-// int data[256+32];
-// FLACCLSubframeTask task;
-// } shared;
-// const int tid = get_local_id(0) + (get_local_id(1) << 4);
-// if (tid < sizeof(shared.task) / sizeof(int))
-// ((int*)&shared.task)[tid] = ((int*)(&tasks[get_group_id(1)]))[tid];
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// const int offs = (get_group_id(0) << 8) + tid;
-//
-// // fetch samples
-// if (tid < 32) shared.data[tid] = min(offs, tid + shared.task.data.residualOrder) >= 32 ? samples[shared.task.data.samplesOffs + offs - 32] >> shared.task.data.wbits : 0;
-// shared.data[32 + tid] = samples[shared.task.data.samplesOffs + offs] >> shared.task.data.wbits;
-// // if (tid < 32 && tid >= shared.task.data.residualOrder)
-// //shared.task.coefs[tid] = 0;
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// // compute residual
-// int s = 0;
-// for (int c = -shared.task.data.residualOrder; c < 0; c++)
-// s += __mul24(shared.data[32 + tid + c], shared.task.coefs[shared.task.data.residualOrder + c]);
-// // int spos = 32 + tid - shared.task.data.residualOrder;
-// // int s=
-// //__mul24(shared.data[spos + 0], shared.task.coefs[0]) + __mul24(shared.data[spos + 1], shared.task.coefs[1]) +
-// //__mul24(shared.data[spos + 2], shared.task.coefs[2]) + __mul24(shared.data[spos + 3], shared.task.coefs[3]) +
-// //__mul24(shared.data[spos + 4], shared.task.coefs[4]) + __mul24(shared.data[spos + 5], shared.task.coefs[5]) +
-// //__mul24(shared.data[spos + 6], shared.task.coefs[6]) + __mul24(shared.data[spos + 7], shared.task.coefs[7]) +
-// //__mul24(shared.data[spos + 8], shared.task.coefs[8]) + __mul24(shared.data[spos + 9], shared.task.coefs[9]) +
-// //__mul24(shared.data[spos + 10], shared.task.coefs[10]) + __mul24(shared.data[spos + 11], shared.task.coefs[11]) +
-// //__mul24(shared.data[spos + 12], shared.task.coefs[12]) + __mul24(shared.data[spos + 13], shared.task.coefs[13]) +
-// //__mul24(shared.data[spos + 14], shared.task.coefs[14]) + __mul24(shared.data[spos + 15], shared.task.coefs[15]);
-// s = shared.data[32 + tid] - (s >> shared.task.data.shift);
-//
-// if (get_group_id(0) != 0 || tid >= shared.task.data.residualOrder)
-// residual[shared.task.data.residualOffs + (get_group_id(0) << 8) + tid] = s;
-// else
-// s = 0;
-//
-// // convert to unsigned
-// s = min(0xfffff, (s << 1) ^ (s >> 31));
-// barrier(CLK_LOCAL_MEM_FENCE);
-// shared.data[tid + get_local_id(1)] = s;
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// // calc number of unary bits for part get_local_id(0) with rice paramater get_local_id(1)
-// int dpos = __mul24(get_local_id(0), 17);
-// int sum =
-// (shared.data[dpos + 0] >> get_local_id(1)) + (shared.data[dpos + 1] >> get_local_id(1)) +
-// (shared.data[dpos + 2] >> get_local_id(1)) + (shared.data[dpos + 3] >> get_local_id(1)) +
-// (shared.data[dpos + 4] >> get_local_id(1)) + (shared.data[dpos + 5] >> get_local_id(1)) +
-// (shared.data[dpos + 6] >> get_local_id(1)) + (shared.data[dpos + 7] >> get_local_id(1)) +
-// (shared.data[dpos + 8] >> get_local_id(1)) + (shared.data[dpos + 9] >> get_local_id(1)) +
-// (shared.data[dpos + 10] >> get_local_id(1)) + (shared.data[dpos + 11] >> get_local_id(1)) +
-// (shared.data[dpos + 12] >> get_local_id(1)) + (shared.data[dpos + 13] >> get_local_id(1)) +
-// (shared.data[dpos + 14] >> get_local_id(1)) + (shared.data[dpos + 15] >> get_local_id(1));
-//
-// // output length
-// const int pos = ((15 * get_group_id(1) + get_local_id(1)) << (max_porder + 1)) + (get_group_id(0) << 4) + get_local_id(0);
-// if (get_local_id(1) <= 14)
-// partition_lengths[pos] = sum + (16 - shared.task.data.residualOrder * (get_local_id(0) + get_group_id(0) == 0)) * (get_local_id(1) + 1);
-//}
-//
-//__kernel void cudaCalcLargePartition(
-// int* partition_lengths,
-// int* residual,
-// int* samples,
-// FLACCLSubframeTask *tasks,
-// int max_porder, // <= 8
-// int psize, // == >= 128
-// int parts_per_block // == 1
-// )
-//{
-// __local struct {
-// int data[256];
-// volatile int length[256];
-// FLACCLSubframeTask task;
-// } shared;
-// const int tid = get_local_id(0) + (get_local_id(1) << 4);
-// if (tid < sizeof(shared.task) / sizeof(int))
-// ((int*)&shared.task)[tid] = ((int*)(&tasks[get_group_id(1)]))[tid];
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// int sum = 0;
-// for (int pos = 0; pos < psize; pos += 256)
-// {
-// // fetch residual
-// int offs = get_group_id(0) * psize + pos + tid;
-// int s = (offs >= shared.task.data.residualOrder && pos + tid < psize) ? residual[shared.task.data.residualOffs + offs] : 0;
-// // convert to unsigned
-// shared.data[tid] = min(0xfffff, (s << 1) ^ (s >> 31));
-// barrier(CLK_LOCAL_MEM_FENCE);
-//
-// // calc number of unary bits for each residual sample with each rice paramater
-//#pragma unroll 0
-// for (int i = get_local_id(0); i < min(psize,256); i += 16)
-// // for sample (i + get_local_id(0)) with this rice paramater (get_local_id(1))
-// sum += shared.data[i] >> get_local_id(1);
-// barrier(CLK_LOCAL_MEM_FENCE);
-// }
-// shared.length[tid] = min(0xfffff,sum);
-// SUM16(shared.length,tid,+=);
-//
-// // output length
-// const int pos = (15 << (max_porder + 1)) * get_group_id(1) + (get_local_id(1) << (max_porder + 1));
-// if (get_local_id(1) <= 14 && get_local_id(0) == 0)
-// partition_lengths[pos + get_group_id(0)] = min(0xfffff,shared.length[tid]) + (psize - shared.task.data.residualOrder * (get_group_id(0) == 0)) * (get_local_id(1) + 1);
-//}
-//
+__kernel __attribute__((reqd_work_group_size(GROUP_SIZE, 1, 1)))
+void cudaEncodeResidual(
+ __global int *output,
+ __global int *samples,
+ __global FLACCLSubframeTask *tasks
+ )
+{
+ __local FLACCLSubframeTask task;
+ __local int data[GROUP_SIZE * 2];
+ const int tid = get_local_id(0);
+ if (get_local_id(0) < sizeof(task) / sizeof(int))
+ ((__local int*)&task)[get_local_id(0)] = ((__global int*)(&tasks[get_group_id(1)]))[get_local_id(0)];
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ int bs = task.data.blocksize;
+ int ro = task.data.residualOrder;
+
+ data[tid] = tid < bs ? samples[task.data.samplesOffs + tid] >> task.data.wbits : 0;
+ for (int pos = 0; pos < bs; pos += GROUP_SIZE)
+ {
+ // fetch samples
+ float nextData = pos + tid + GROUP_SIZE < bs ? samples[task.data.samplesOffs + pos + tid + GROUP_SIZE] >> task.data.wbits : 0;
+ data[tid + GROUP_SIZE] = nextData;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // compute residual
+ int sum = 0;
+ for (int c = 0; c < ro; c++)
+ sum += data[tid + c] * task.coefs[c];
+ sum = data[tid + ro] - (sum >> task.data.shift);
+ if (pos + tid + ro < bs)
+ output[task.data.residualOffs + pos + tid + ro] = sum;
+
+ barrier(CLK_LOCAL_MEM_FENCE);
+ data[tid] = nextData;
+ }
+}
+
+__kernel __attribute__((reqd_work_group_size(GROUP_SIZE, 1, 1)))
+void cudaCalcPartition(
+ __global int *partition_lengths,
+ __global int *residual,
+ __global FLACCLSubframeTask *tasks,
+ int max_porder, // <= 8
+ int psize // == task.blocksize >> max_porder?
+ )
+{
+ __local int data[GROUP_SIZE];
+ __local int length[GROUP_SIZE / 16][16];
+ __local FLACCLSubframeData task;
+
+ 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];
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ int k = tid % (GROUP_SIZE / 16);
+ int x = tid / (GROUP_SIZE / 16);
+
+ int sum = 0;
+ for (int pos0 = 0; pos0 < psize; pos0 += GROUP_SIZE)
+ {
+ int offs = get_group_id(0) * psize + pos0 + tid;
+ // fetch residual
+ int s = (offs >= task.residualOrder && pos0 + tid < psize) ? residual[task.residualOffs + offs] : 0;
+ // convert to unsigned
+ data[tid] = min(0xfffff, (s << 1) ^ (s >> 31));
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // calc number of unary bits for each residual sample with each rice paramater
+ for (int pos = 0; pos < psize && pos < GROUP_SIZE; pos += GROUP_SIZE / 16)
+ sum += data[pos + x] >> k;
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+
+ length[x][k] = min(0xfffff, sum);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ if (x == 0)
+ {
+ for (int i = 1; i < GROUP_SIZE / 16; i++)
+ length[0][k] += length[i][k];
+ // output length
+ const int pos = (15 << (max_porder + 1)) * get_group_id(1) + (k << (max_porder + 1));
+ if (k <= 14)
+ partition_lengths[pos + get_group_id(0)] = min(0xfffff,length[0][k]) + (psize - task.residualOrder * (get_group_id(0) == 0)) * (k + 1);
+ }
+}
+
//// Sums partition lengths for a certain k == get_group_id(0)
//// Requires 128 threads
//__kernel void cudaSumPartition(