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Fixed potential overflows in SVM, minor adjustments to nvtx ranges #5504

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Jul 17, 2023
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Fixed potential overflows in SVM, minor adjustments to nvtx ranges #5504

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4 changes: 2 additions & 2 deletions cpp/src/svm/kernelcache.cuh
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Original file line number Diff line number Diff line change
Expand Up @@ -362,7 +362,7 @@ class KernelCache {
batch_size_base = n_rows;

// enable batching for kernel > 1 GB (default)
if (n_rows * n_ws * sizeof(math_t) > kernel_tile_byte_limit) {
if ((size_t)n_rows * n_ws * sizeof(math_t) > kernel_tile_byte_limit) {
batching_enabled = true;
// only select based on desired big-kernel size
batch_size_base = std::max(1ul, kernel_tile_byte_limit / n_ws / sizeof(math_t));
Expand All @@ -373,7 +373,7 @@ class KernelCache {

// enable sparse row extraction for sparse input where n_ws * n_cols > 1 GB
// Warning: kernel computation will be much slower!
if (is_csr && (n_cols * n_ws * sizeof(math_t) > dense_extract_byte_limit)) {
if (is_csr && ((size_t)n_cols * n_ws * sizeof(math_t) > dense_extract_byte_limit)) {
sparse_extract = true;
}

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3 changes: 2 additions & 1 deletion cpp/src/svm/results.cuh
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Expand Up @@ -143,7 +143,8 @@ class Results {
{
SupportStorage<math_t> support_matrix;
// allow ~1GB dense support matrix
if (isDenseType<MatrixViewType>() || (n_support * n_cols * sizeof(math_t) < (1 << 30))) {
if (isDenseType<MatrixViewType>() ||
((size_t)n_support * n_cols * sizeof(math_t) < (1 << 30))) {
support_matrix.data =
(math_t*)rmm_alloc->allocate(n_support * n_cols * sizeof(math_t), stream);
ML::SVM::extractRows<math_t>(matrix, support_matrix.data, idx, n_support, handle);
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6 changes: 3 additions & 3 deletions cpp/src/svm/smosolver.cuh
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Expand Up @@ -221,6 +221,7 @@ class SmoSolver {
raft::update_host(host_return_buff, return_buff.data(), 2, stream);
raft::common::nvtx::pop_range();
raft::common::nvtx::push_range("SmoSolver::UpdateF");
raft::common::nvtx::push_range("SmoSolver::UpdateF::getNnzDaRows");
int nnz_da;
GetNonzeroDeltaAlpha(delta_alpha.data(),
n_ws,
Expand All @@ -232,11 +233,10 @@ class SmoSolver {
RAFT_CUDA_TRY(cudaPeekAtLastError());
// The following should be performed only for elements with nonzero delta_alpha
if (nnz_da > 0) {
raft::common::nvtx::push_range("SmoSolver::UpdateF::getNnzDaRows");
auto batch_descriptor = cache.InitFullTileBatching(nz_da_idx.data(), nnz_da);
raft::common::nvtx::pop_range();

while (cache.getNextBatchKernel(batch_descriptor)) {
raft::common::nvtx::pop_range();
raft::common::nvtx::push_range("SmoSolver::UpdateF::updateBatch");
// do (partial) update
UpdateF(f.data() + batch_descriptor.offset,
Expand All @@ -245,10 +245,10 @@ class SmoSolver {
nnz_da,
batch_descriptor.kernel_data);
RAFT_CUDA_TRY(cudaPeekAtLastError());
raft::common::nvtx::pop_range();
}
}
handle.sync_stream(stream);
raft::common::nvtx::pop_range();
raft::common::nvtx::pop_range(); // ("SmoSolver::UpdateF");

math_t diff = host_return_buff[0];
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3 changes: 2 additions & 1 deletion cpp/src/svm/svc_impl.cuh
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Expand Up @@ -93,6 +93,7 @@ void svcFitX(const raft::handle_t& handle,
&(model.b),
param.max_iter);
model.n_cols = n_cols;
handle_impl.sync_stream(stream);
delete kernel;
}

Expand Down Expand Up @@ -150,7 +151,7 @@ void svcPredictX(const raft::handle_t& handle,
int n_batch = n_rows;
// Limit the memory size of the prediction buffer
buffer_size = buffer_size * 1024 * 1024;
if (n_batch * model.n_support * sizeof(math_t) > buffer_size) {
if ((size_t)n_batch * model.n_support * sizeof(math_t) > buffer_size) {
n_batch = buffer_size / (model.n_support * sizeof(math_t));
if (n_batch < 1) n_batch = 1;
}
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2 changes: 1 addition & 1 deletion python/cuml/svm/svc.pyx
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Expand Up @@ -529,7 +529,7 @@ class SVC(SVMBase,
cdef int n_rows = self.n_rows
cdef int n_cols = self.n_cols

cdef int n_nnz = X_m.nnz if is_sparse else self.n_rows * self.n_cols
cdef int n_nnz = X_m.nnz if is_sparse else -1
cdef uintptr_t X_indptr = X_m.indptr.ptr if is_sparse else X_m.ptr
cdef uintptr_t X_indices = X_m.indices.ptr if is_sparse else X_m.ptr
cdef uintptr_t X_data = X_m.data.ptr if is_sparse else X_m.ptr
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2 changes: 1 addition & 1 deletion python/cuml/svm/svr.pyx
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Expand Up @@ -295,7 +295,7 @@ class SVR(SVMBase, RegressorMixin):

cdef int n_rows = self.n_rows
cdef int n_cols = self.n_cols
cdef int n_nnz = X_m.nnz if is_sparse else self.n_rows * self.n_cols
cdef int n_nnz = X_m.nnz if is_sparse else -1
cdef uintptr_t X_indptr = X_m.indptr.ptr if is_sparse else X_m.ptr
cdef uintptr_t X_indices = X_m.indices.ptr if is_sparse else X_m.ptr
cdef uintptr_t X_data = X_m.data.ptr if is_sparse else X_m.ptr
Expand Down