/**
* Return the value the head should take if some propagation is possible.
*/
lbool MinisatID::canPropagateHead(const Agg& agg, const Weight& CC, const Weight& CP) {
//if (nomoreprops[agg.getIndex()] || headproptime[agg.getIndex()]!=-1) {
// return headvalue[agg.getIndex()];
//}
auto result = l_Undef;
//add if derived: headproptime[agg.getIndex()] = getStack().size();
auto b = agg.getBound();
if (agg.hasUB()) {
if (CC > b) {
result = l_False;
} else if (CP <= b) {
result = l_True;
}
} else {
if (CC >= b) {
result = l_True;
} else if (CP < b) {
result = l_False;
}
}
if(agg.getSem()==AggSem::OR){
if(result==l_True){
result = l_Undef;
}else if(result==l_False){
result = l_True;
}
}
return result;
}
__global__ void kAggShortRows(const float* mat, float* matSum, const uint width, const uint height, Agg agg, UnaryOp uop, BinaryOp bop) {
const uint shmemX = THREADS_X + 1;
__shared__ float shmem[AGG_SHORT_ROWS_THREADS_Y*shmemX];
const uint tidx = hipThreadIdx_y * THREADS_X + hipThreadIdx_x;
const uint ty = LOOPS_X == 1 ? tidx / width : hipThreadIdx_y; // when loops==1, width is gonna be smaller than block x dim
const uint tx = LOOPS_X == 1 ? tidx % width : hipThreadIdx_x;
const uint bidx = hipBlockIdx_y * hipGridDim_x + hipBlockIdx_x;
const uint blockRowIdx = bidx * AGG_SHORT_ROWS_LOOPS_Y * AGG_SHORT_ROWS_THREADS_Y;
float* shmemWrite = shmem + MUL24(ty, shmemX) + tx;
matSum += blockRowIdx + tidx;
// shmem[MUL24(hipThreadIdx_y, shmemX) + hipThreadIdx_x] = 0;
mat += width * blockRowIdx + MUL24(ty, width) + tx;
float* shmemWriteZeros = &shmem[MUL24(hipThreadIdx_y,shmemX) + hipThreadIdx_x];
bool doAgg = tidx < AGG_SHORT_ROWS_THREADS_Y ;
if (blockRowIdx < height) {
#pragma unroll
for (uint y = 0; y < AGG_SHORT_ROWS_LOOPS_Y*AGG_SHORT_ROWS_THREADS_Y; y += AGG_SHORT_ROWS_THREADS_Y) {
doAgg &= tidx + y + blockRowIdx < height;
const bool heightIdxOK = ty < AGG_SHORT_ROWS_THREADS_Y && ty + y + blockRowIdx < height;
shmemWriteZeros[0] = agg.getBaseValue();
__syncthreads();
#pragma unroll
for(uint x = 0; x < LOOPS_X * THREADS_X; x+= THREADS_X) {
// __syncthreads();
if (heightIdxOK && x + tx < width) {
shmemWrite[0] = agg(uop(mat[x]), shmemWrite[0]);
}
}
__syncthreads();
if (doAgg) {
/*
* I tried doing this final sum as a 4-step reduction, with 8 threads
* per warp participating. It was slightly slower.
*/
float accum = agg.getBaseValue();
float* shmemRead = shmem + MUL24(tidx, shmemX);
// this loops too much if the rows are really short :(
#pragma unroll
for (uint i = 0; i < THREADS_X; i++) {
accum = agg(accum, shmemRead[0]);
shmemRead++;
}
matSum[0] = bop(matSum[0], accum);
matSum += AGG_SHORT_ROWS_THREADS_Y;
}
__syncthreads();
mat += width * AGG_SHORT_ROWS_THREADS_Y;
}
}
}
__global__ void kTotalAgg(const float* a, float* const target, const uint numElements, Agg agg) {
__shared__ float shmem[DP_BLOCKSIZE];
uint eidx = DP_BLOCKSIZE * hipBlockIdx_x + hipThreadIdx_x;
shmem[hipThreadIdx_x] = agg.getBaseValue();
if (eidx < hipGridDim_x * DP_BLOCKSIZE) {
for (; eidx < numElements; eidx += hipGridDim_x * DP_BLOCKSIZE) {
shmem[hipThreadIdx_x] = agg(shmem[hipThreadIdx_x], a[eidx]);
}
}
__syncthreads();
if (hipThreadIdx_x < 256) {
shmem[hipThreadIdx_x] = agg(shmem[hipThreadIdx_x], shmem[hipThreadIdx_x + 256]);
}
__syncthreads();
if (hipThreadIdx_x < 128) {
shmem[hipThreadIdx_x] = agg(shmem[hipThreadIdx_x], shmem[hipThreadIdx_x + 128]);
}
__syncthreads();
if (hipThreadIdx_x < 64) {
shmem[hipThreadIdx_x] = agg(shmem[hipThreadIdx_x], shmem[hipThreadIdx_x + 64]);
}
__syncthreads();
if (hipThreadIdx_x < 32) {
volatile float* mysh = &shmem[hipThreadIdx_x];
*mysh = agg(*mysh, mysh[32]);
*mysh = agg(*mysh, mysh[16]);
*mysh = agg(*mysh, mysh[8]);
*mysh = agg(*mysh, mysh[4]);
*mysh = agg(*mysh, mysh[2]);
*mysh = agg(*mysh, mysh[1]);
if (hipThreadIdx_x == 0) {
target[hipBlockIdx_x] = *mysh;
}
}
}
__global__ void kAggShortRows2(const float* mat, float* matSum, const uint width, const uint height, Agg agg, UnaryOp uop, BinaryOp bop) {
const uint shmemX = AGG_SHORT_ROWS_THREADS_X + 1;
__shared__ float shmem[AGG_SHORT_ROWS_THREADS_Y*shmemX];
const uint LOOPS_X = DIVUP(width, AGG_SHORT_ROWS_THREADS_X);
const uint tidx = hipThreadIdx_y * AGG_SHORT_ROWS_THREADS_X + hipThreadIdx_x;
const uint bidx = hipBlockIdx_y * hipGridDim_x + hipBlockIdx_x;
const uint blockRowIdx = bidx * AGG_SHORT_ROWS_LOOPS_Y * AGG_SHORT_ROWS_THREADS_Y;
float* shmemWrite = shmem + MUL24(hipThreadIdx_y, shmemX) + hipThreadIdx_x;
matSum += blockRowIdx + tidx;
// shmem[MUL24(hipThreadIdx_y, shmemX) + hipThreadIdx_x] = 0;
mat += width * blockRowIdx + MUL24(hipThreadIdx_y, width) + hipThreadIdx_x;
bool doAgg = tidx < AGG_SHORT_ROWS_THREADS_Y;
if(blockRowIdx < height) {
for (uint y = 0; y < AGG_SHORT_ROWS_LOOPS_Y*AGG_SHORT_ROWS_THREADS_Y; y += AGG_SHORT_ROWS_THREADS_Y) {
doAgg &= tidx + y + blockRowIdx < height;
const bool heightIdxOK = hipThreadIdx_y + y + blockRowIdx < height;
float accum = agg.getBaseValue();
shmemWrite[0] = agg.getBaseValue();
for(uint x = 0; x < LOOPS_X * AGG_SHORT_ROWS_THREADS_X; x+= AGG_SHORT_ROWS_THREADS_X) {
// __syncthreads();
if (heightIdxOK && x + hipThreadIdx_x < width) {
shmemWrite[0] = agg(uop(mat[x]), shmemWrite[0]);
}
}
__syncthreads();
if (doAgg) {
float* shmemRead = shmem + MUL24(tidx, shmemX);
#pragma unroll
for (uint i = 0; i < AGG_SHORT_ROWS_THREADS_X; i++) {
accum = agg(accum, shmemRead[0]);
shmemRead++;
}
matSum[0] = bop(matSum[0], accum);
matSum += AGG_SHORT_ROWS_THREADS_Y;
}
__syncthreads();
mat += width * AGG_SHORT_ROWS_THREADS_Y;
}
}
}
/**
* Returns true if this aggregate can be propagated in the initialization, so it will never change truth value
* and can be left out of any propagations.
* Returns false if the aggregate is certainly unsat.
*/
lbool FWAgg::initialize(const Agg& agg) {
auto confl = nullPtrClause;
auto hv = canPropagateHead(agg, getCC(), getCP());
bool alwaystrue = false;
if (hv != l_Undef) {
alwaystrue = true;
}
if (hv == l_True) {
confl = getSet().notifySolver(new HeadReason(agg, agg.getHead()));
} else if (hv == l_False) {
confl = getSet().notifySolver(new HeadReason(agg, not agg.getHead()));
}
if (confl != nullPtrClause) {
return l_False;
}
return alwaystrue ? l_True : l_Undef;
}
__global__ void kDumbAggCols(cudaTextureObject_t mat, float* const vec, const uint width, const uint height, Agg agg, UnaryOp uop, BinaryOp bop) {
const uint idx = hipBlockIdx_x * hipBlockDim_x + hipThreadIdx_x;
if (idx < width) {
float mx = agg.getBaseValue();
for (uint j = 0; j < height; j++) {
mx = agg(uop(tex1Dfetch<float>(mat, width * j + idx)), mx);
}
vec[idx] = bop(vec[idx], mx);
}
}
/**
* Returns non-owning pointer
*/
rClause MaxFWAgg::propagateSpecificAtEnd(const Agg& agg, bool headtrue) {
//if(nomoreprops[agg.getIndex()] || headproptime[agg.getIndex()]!=-1){ return nullPtrClause; }
auto confl = nullPtrClause;
if (headtrue && agg.hasUB()) {
for (auto i = getSet().getWL().rbegin(); confl == nullPtrClause && i < getSet().getWL().rend() && agg.getBound() < i->getWeight();
++i) {
confl = getSet().notifySolver(new SetLitReason(agg, i->getLit(), i->getWeight(), false));
}
} else if (!headtrue && agg.hasLB()) {
for (auto i = getSet().getWL().rbegin(); confl == nullPtrClause && i < getSet().getWL().rend() && agg.getBound() <= i->getWeight();
++i) {
confl = getSet().notifySolver(new SetLitReason(agg, i->getLit(), i->getWeight(), false));
}
}
if (confl == nullPtrClause) {
confl = propagateAll(agg, headtrue);
}
return confl;
}
__global__ void kAggCols(cudaTextureObject_t mat, float* const vec, const uint width, const uint height, const uint sumLength, Agg agg, UnaryOp op) {
const uint idxX = hipBlockIdx_x * hipBlockDim_x + hipThreadIdx_x;
const uint idxY = hipBlockIdx_y * sumLength;
if (idxX < width) {
float mx = agg.getBaseValue();
for (uint j = idxY; j < min(height,idxY + sumLength); j++) {
mx = agg(op(tex1Dfetch<float>(mat, j * width + idxX)), mx);
}
vec[hipBlockIdx_y * width + idxX] = mx;
}
}
// Can return NULL, if no heads are false (or unknown if includeunknown)
Agg* GenPWAgg::getAggWithMostStringentBound(bool includeunknown) const {
Agg* strongestagg = NULL;
for (auto i = getAgg().cbegin(); i < getAgg().cend(); ++i) {
bool relevantagg = false; // NOTE: recall HEAD OR AGG
if (includeunknown) {
relevantagg |= value((*i)->getHead()) != l_True;
} else {
relevantagg |= value((*i)->getHead()) == l_False;
}
if (relevantagg) {
if (strongestagg == NULL) {
strongestagg = *i;
} else if (strongestagg->hasLB() && strongestagg->getBound() < (*i)->getBound()) {
strongestagg = *i;
} else if (strongestagg->hasUB() && strongestagg->getBound() > (*i)->getBound()) {
strongestagg = *i;
}
}
}
return strongestagg;
}
/**
* Returns non-owning pointer
*/
rClause MaxFWAgg::propagateAll(const Agg& agg, bool headtrue) {
rClause confl = nullPtrClause;
// if(nomoreprops[agg.getIndex()] || headproptime[agg.getIndex()]!=-1){ return confl; }
if ((!agg.hasLB() && headtrue) || (!agg.hasUB() && !headtrue)) {
return confl;
}
Lit l = mkPosLit(0);
Weight w(0);
int found = 0;
for (vwl::const_iterator i = getSet().getWL().cbegin(); found < 2 && i < getSet().getWL().cend(); ++i) {
const WL& wl = (*i);
if (headtrue) {
if (agg.hasLB() && wl.getWeight() < agg.getBound()) {
continue;
}
if (agg.hasUB() && wl.getWeight() > agg.getBound()) {
continue;
}
} else { //headfalse
if ((!agg.hasLB() || wl.getWeight() >= agg.getBound()) && (!agg.hasUB() || wl.getWeight() <= agg.getBound())) {
continue;
}
}
if (value(wl.getLit()) == l_Undef) {
++found;
l = wl.getLit();
w = wl.getWeight();
} else if (value(wl.getLit()) == l_True) {
found = 2; //hack to stop immediately, because no propagation necessary
}
}
if (found == 1) {
confl = getSet().notifySolver(new SetLitReason(agg, l, w, true));
}
return confl;
}
__global__ void kAggRows_wholerow_nosync(const float* mat, float* matSum, const uint width, const uint height,
Agg agg, UnaryOp uop, BinaryOp bop) {
const uint tidx = hipThreadIdx_x;
const uint warpIdx = tidx / WARP_SIZE;
const uint lane = tidx % WARP_SIZE;
__shared__ float accum[(WARP_SIZE + 1) * AWR_NUM_WARPS];
__shared__ float finalAccum[AWR_NUM_WARPS];
float* myAccum = &accum[warpIdx * (WARP_SIZE + 1) + lane];
float* myFinalAccum = &finalAccum[tidx];
//volatile float* vMyAccum = &accum[warpIdx * (WARP_SIZE + 1) + lane];
matSum += hipBlockIdx_y;
mat += width * hipBlockIdx_y;
float rAccum = agg.getBaseValue(); // cache in register, a bit faster than shmem
#pragma unroll 32
for (uint x = tidx; x < width; x += AWR_NUM_THREADS) {
rAccum = agg(rAccum, uop(mat[x]));
}
myAccum[0] = rAccum;
// Each warp does a reduction that doesn't require synchronizatoin
#pragma unroll
for (uint i = 0; i < LOG_WARP_SIZE; i++) {
const uint d = 1 << i;
myAccum[0] = agg(myAccum[0], shfl_down(myAccum[0], d));
}
__syncthreads();
// The warps write their results
if (tidx < AWR_NUM_WARPS) {
//volatile float* vMyFinalAccum = &finalAccum[tidx];
myFinalAccum[0] = accum[tidx * (WARP_SIZE + 1)];
#pragma unroll
for (uint i = 0; i < AWR_LOG_NUM_WARPS; i++) {
const uint d = 1 << i;
myFinalAccum[0] = agg(myFinalAccum[0], shfl_down(myFinalAccum[0], d));
}
if (tidx == 0) {
matSum[0] = bop(matSum[0], myFinalAccum[0]);
matSum += hipGridDim_y;
}
}
}
rClause GenPWAgg::checkHeadPropagationForAgg(bool& propagations, const Agg& agg, const minmaxBounds& bound) {
auto confl = nullPtrClause;
auto propagatehead = false;
if (agg.hasLB() && bound.max < agg.getBound()) {
propagatehead = true;
} else if (agg.hasUB() && agg.getBound() < bound.min) {
propagatehead = true;
}
if (propagatehead) {
propagations = true;
confl = getSet().notifySolver(new HeadReason(agg, agg.getHead()));
notifyFirstPropagation(agg.getHead());
}
return confl;
}
__global__ void kAggRows_wholerow(const float* mat, float* matSum, const uint width, const uint height, Agg agg, BinaryOp op) {
const int tidx = hipThreadIdx_x;
__shared__ float accum[AWR_NUM_THREADS];
volatile float* vMyAccum = &accum[tidx];
float* myAccum = &accum[tidx];
matSum += hipBlockIdx_y;
mat += width * hipBlockIdx_y;
for (uint idxY = hipBlockIdx_y; idxY < height; idxY += hipGridDim_y) {
myAccum[0] = agg.getBaseValue();
for (uint x = tidx; x < width; x += AWR_NUM_THREADS) {
myAccum[0] = agg(myAccum[0], mat[x]);
}
#pragma unroll
for (uint i = AWR_LOG_NUM_THREADS - 1; i > LOG_WARP_SIZE; i--) {
const uint d = 1 << i;
__syncthreads();
if (tidx < d) {
myAccum[0] = agg(myAccum[0], myAccum[d]);
}
}
__syncthreads();
if (tidx < WARP_SIZE) {
#pragma unroll
for (int i = LOG_WARP_SIZE; i >= 0; i--) {
const uint d = 1 << i;
vMyAccum[0] = agg(vMyAccum[0], vMyAccum[d]);
}
if (tidx == 0) {
matSum[0] = op(matSum[0], vMyAccum[0]);
matSum += hipGridDim_y;
}
}
__syncthreads();
mat += width * hipGridDim_y;
}
}
/**
* if headtrue && lb => make all literals true with weight > (CP - lb)
* ub => make all literals false with weight > (ub - CC)
* if !headtrue && lb => make all literals false with weight > (lb - CC)
* ub => make all literals true with weight > (CP - ub)
* if both bounds: do both for headtrue
* do none for headfalse until cc >= lb or cp <= ub
*/
rClause SPFWAgg::propagateSpecificAtEnd(const Agg& agg, bool headtrue) {
rClause c = nullPtrClause;
//if (nomoreprops[agg.getIndex()] || headproptime[agg.getIndex()]!=-1) {
// return nullPtrClause;
//}
auto& set = getSet();
const auto& wls = set.getWL();
auto from = wls.cend();
Weight weightbound;
bool ub = agg.hasUB();
auto bound = agg.getBound();
//determine the lower bound of which weight literals to consider
const AggProp& type = getSet().getType();
if (headtrue) {
if (ub) {
weightbound = type.removeMin(bound, getCC());
//+1 because larger and not eq
if (type.add(weightbound, getCC()) <= bound) {
weightbound += 1;
}
} else {
weightbound = type.removeMax(getCP(), bound);
//+1 because larger and not eq
if (type.add(weightbound, bound) <= getCP()) {
weightbound += 1;
}
}
} else { //head false
if (ub) {
weightbound = type.removeMax(getCP(), bound);
} else {
weightbound = type.removeMin(bound, getCC());
}
}
#ifdef NOARBITPREC
if (weightbound == posInfinity() || weightbound == negInfinity()) {
return c;
}
#endif
from = lower_bound(wls.cbegin(), wls.cend(), weightbound);
if (from == getSet().getWL().cend()) {
return c;
}
/**
* The lower bound indicates from which bound all literals should be propagate that are not yet known to the aggregate solver
* All literals known to the sat solver are certainly sa
*/
for (auto u = from; c == nullPtrClause && u < wls.cend(); ++u) {
auto l = (*u).getLit();
bool propagate = value(l) == l_Undef;
if (!propagate && getSet().getPCSolver().getLevel(var(l)) == getSet().getPCSolver().getCurrentDecisionLevel()) {
bool found = false;
for (auto i = getTrail().back()->props.cbegin(); !found && i < getTrail().back()->props.cend(); ++i) {
if (var(l) == var(i->getLit())) {
found = true;
}
}
propagate = !found;
}
//Only propagate those that are not already known in the aggregate solver!
if (propagate) {
if ((agg.hasUB() && headtrue) || (!agg.hasUB() && !headtrue)) {
c = getSet().notifySolver(new SetLitReason(agg, (*u).getLit(), (*u).getWeight(), false));
} else {
c = getSet().notifySolver(new SetLitReason(agg, (*u).getLit(), (*u).getWeight(), true));
}
}
}
//TODO the looping over the trail is TOO slow! compared to old card
//TODO but bigger problem is that he keeps on deriving the same propagations!
//=> add a check that does not do propagations if the derived weight bound is the same
//=> add a check that if only cp or cc is adapted, only aggs with such bound are checked!
return c;
}
__global__ void kAggRows(const float* mat, float* matSum, const uint width, const uint height, const uint sumWidth, Agg agg, UnaryOp uop, BinaryOp bop) {
const int idxX = hipBlockIdx_x * blockSize*2 + hipThreadIdx_x;
__shared__ float accum[blockSize*2];
matSum += hipBlockIdx_y * sumWidth + hipBlockIdx_x;
/*
* Here it's important to make sure that all threads in a block call __syncthreads,
* so I have even the redundant threads (for which idxX >= width) enter this loop
* just so that they may call __syncthreads at the appropriate times.
*/
mat += width * hipBlockIdx_y + idxX;
accum[hipThreadIdx_x] = agg.getBaseValue();
accum[hipThreadIdx_x + blockSize] = agg.getBaseValue();
for (uint idxY = hipBlockIdx_y; idxY < height; idxY += hipGridDim_y) {
if (idxX < width) {
accum[hipThreadIdx_x] = uop(mat[0]);
if(idxX + blockSize < width)
accum[hipThreadIdx_x + blockSize] = uop(mat[blockSize]);
}
if (blockSize >= 512) {
__syncthreads();
if (hipThreadIdx_x < 512)
accum[hipThreadIdx_x] = agg(accum[hipThreadIdx_x], accum[hipThreadIdx_x + 512]);
}
if (blockSize >= 256) {
__syncthreads();
if (hipThreadIdx_x < 256)
accum[hipThreadIdx_x] = agg(accum[hipThreadIdx_x],accum[hipThreadIdx_x + 256]);
}
if (blockSize >= 128) {
__syncthreads();
if (hipThreadIdx_x < 128)
accum[hipThreadIdx_x] = agg(accum[hipThreadIdx_x],accum[hipThreadIdx_x + 128]);
}
if (blockSize >= 64) {
__syncthreads();
if (hipThreadIdx_x < 64)
accum[hipThreadIdx_x] = agg(accum[hipThreadIdx_x],accum[hipThreadIdx_x + 64]);
}
__syncthreads();
volatile float* myAccum = &accum[hipThreadIdx_x];
if (hipThreadIdx_x < 32) { // executed only by first warp
myAccum[0] = agg(myAccum[0], myAccum[32]);
myAccum[0] = agg(myAccum[0], myAccum[16]);
myAccum[0] = agg(myAccum[0], myAccum[8]);
myAccum[0] = agg(myAccum[0], myAccum[4]);
myAccum[0] = agg(myAccum[0], myAccum[2]);
myAccum[0] = agg(myAccum[0], myAccum[1]);
}
if (hipThreadIdx_x == 0) {
matSum[0] = bop(matSum[0], myAccum[0]);
matSum += hipGridDim_y * sumWidth;
}
__syncthreads();
mat += width * hipGridDim_y;
}
}