Comments (5)
This confuses me. cudaTextureObject_t is an unsigned long long, so the
comparison with zero should be fine. I'll need more details to reproduce this.
I've never seen it myself.
Original comment by [email protected]
on 4 Aug 2014 at 6:40
from cuda-convnet2.
I can't upload snapshot, so list related code as fellow :
1458 cudaTextureObject_t NVMatrix::getTextureObject() {
1459 if (_texObj == 0) {
1460 assert(isContiguous());
1461 //size_t memFree, memTotal;
1462
1463 struct cudaResourceDesc resDesc;
1464 memset(&resDesc, 0, sizeof(resDesc));
1465 resDesc.resType = cudaResourceTypeLinear;
1466 resDesc.res.linear.devPtr = getDevData();
1467 resDesc.res.linear.sizeInBytes = getNumDataBytes();
1468 resDesc.res.linear.desc = cudaCreateChannelDesc(32, 0, 0, 0,
cudaChannelFormatKindFloat);
1469 struct cudaTextureDesc texDesc;
1470 memset(&texDesc, 0, sizeof(texDesc));
1471 checkCudaErrors(cudaCreateTextureObject(&_texObj, &resDesc, &texDesc, NULL));
1472 }
1473 assert(_texObj != 0);
1474 return _texObj;
1475 }
_texObj returned by line 1471 is ok if it is zero, but that will make line 1473
fail.
Original comment by [email protected]
on 5 Aug 2014 at 1:41
from cuda-convnet2.
Oh, so you're saying that 0 is a valid value for _texObj that might be set by
cudaCreateTextureObject. I didn't realize this. I'll have to work around that
somehow then. Thanks.
Original comment by [email protected]
on 11 Aug 2014 at 6:30
from cuda-convnet2.
I think why you using cudaTextureObject_t is because you want to
utilize readonly cache in GK110. Another way to use the readonly cache
is using const __restrict__ pointer, such as const float* __restrict__
images. that will solve this bug, and resolve the memory amount
limitation problem of texture and makes code looks better
hope that information will hope.
BTW, I have worked at Baidu Company for six months, my boss is Ren Wu,
he say you are his friend:).
于 2014/8/12 星期二 2:30, [email protected] 写道:
Original comment by [email protected]
on 12 Aug 2014 at 12:48
from cuda-convnet2.
Texture memory is (for mysterious reasons) still pretty noticeably faster than
__restrict__ pointers in the cases where I use it, but I'll keep this in mind,
thanks.
Original comment by [email protected]
on 12 Aug 2014 at 6:27
from cuda-convnet2.
Related Issues (14)
- Memory limits due to texture memory HOT 12
- GTX7XX support
- Element wise sum not working as expected HOT 1
- Remove NPY deprecated warnings
- Error: cannot allocate memory for thread-local data: ABORT
- conv1 weights and biases become nan
- Benchmark on CUDA 6.5 HOT 1
- (nvmatrix.cu) Kernel execution failed error with cuda5.5 HOT 3
- cost.sum2 crash HOT 1
- saving multiview predictions (--test-out) does not work HOT 1
- Loading all data in shownet
- Multiple data layer with binomialcrossEntropyCostLayer HOT 1
- Does not work on 8 GPUs
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