Skip to content

Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ptrendx merged 1 commit into from
Jan 27, 2023
Merged

Fix the integer overflow in fused softmax #60

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
29 changes: 17 additions & 12 deletions transformer_engine/common/fused_softmax/scaled_masked_softmax.cu
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

// blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
// gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
+ threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
(blockIdx.y + gridDim.y * blockIdx.z))
+ threadIdx.y) * WARP_BATCH;

// micro_batch_size might not be a multiple of WARP_BATCH. Check how
// many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
// there might be multiple batches per warp. compute the index within the batch
int local_idx = threadIdx.x;

src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
src += thread_offset;
dst += thread_offset;

// load data from global memory
acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

// blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
// gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
+ threadIdx.y) * WARP_BATCH;
int pad_first_batch = 0;
size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
(blockIdx.y + gridDim.y * blockIdx.z))
+ threadIdx.y) * WARP_BATCH;
size_t pad_first_batch = 0;
if (pad_batches != 1) { // bert style
pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
* WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
// there might be multiple batches per warp. compute the index within the batch
int local_idx = threadIdx.x;

src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
src += thread_offset_src_dst;
dst += thread_offset_src_dst;
mask += thread_offset_mask;

// load data from global memory
acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

// blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
// gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

// micro_batch_size might not be a multiple of WARP_BATCH. Check how
// many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
int local_idx = threadIdx.x;

// the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
grad += thread_offset;
output += thread_offset;
gradInput += thread_offset;
Expand Down
13 changes: 8 additions & 5 deletions transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
+ blockIdx.x;
int local_seq = blockIdx.x + 1;
int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
// there might be multiple batches per warp. compute the index within the batch
int local_idx = threadIdx.x;

src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
src += thread_offset;
dst += thread_offset;

// load data from global memory
acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
+ blockIdx.x;
int local_seq = blockIdx.x + 1;

// micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
int local_idx = threadIdx.x;

// the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
grad += thread_offset;
output += thread_offset;
gradInput += thread_offset;
Expand Down
4 changes: 4 additions & 0 deletions transformer_engine/pytorch/csrc/extensions.cu
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
(input.scalar_type() == at::ScalarType::BFloat16),
"Only fp16 and bf16 are supported");
AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
if (!input.is_contiguous())
input = input.contiguous();
if (!mask.is_contiguous())
mask = mask.contiguous();

const int batches = input.size(0);
const int pad_batches = mask.size(0);
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
 blocks
(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
Fix the integer overflow in fused softmax by ptrendx · Pull Request #60 · NVIDIA/TransformerEngine · GitHub
Skip to content
Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

ptrendx
merged 1 commit into

from

Jan 27, 2023
 Merged


Fix the integer overflow in fused softmax
#60
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


29 changes: 17 additions & 12 deletions
transformer_engine/common/fused_softmax/scaled_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 int pad_first_batch = 0;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t pad_first_batch = 0;
 if (pad_batches != 1) { // bert style
 pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
 * WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset_src_dst;
 dst += thread_offset_src_dst;
 mask += thread_offset_mask;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

13 changes: 8 additions & 5 deletions
transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;
 int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

4 changes: 4 additions & 0 deletions
transformer_engine/pytorch/csrc/extensions.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
 (input.scalar_type() == at::ScalarType::BFloat16),
 "Only fp16 and bf16 are supported");
 AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
 if (!input.is_contiguous())
 input = input.contiguous();
 if (!mask.is_contiguous())
 mask = mask.contiguous();

 const int batches = input.size(0);
 const int pad_batches = mask.size(0);
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
(function() {
var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
}
.markdown-body pre { background: #161b22 !important; }
.markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }
.markdown-body table th, .markdown-body table td { border-color: #30363d !important; }
.markdown-body img { background: #0d1117; }
.markdown-body blockquote { border-left-color: #8b949e; }
.markdown-body hr { border-color: #30363d; }
';
document.head.appendChild(style);
})();
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Fix the integer overflow in fused softmax by ptrendx · Pull Request #60 · NVIDIA/TransformerEngine · GitHub
Skip to content
Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

ptrendx
merged 1 commit into

from

Jan 27, 2023
 Merged


Fix the integer overflow in fused softmax
#60
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


29 changes: 17 additions & 12 deletions
transformer_engine/common/fused_softmax/scaled_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 int pad_first_batch = 0;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t pad_first_batch = 0;
 if (pad_batches != 1) { // bert style
 pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
 * WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset_src_dst;
 dst += thread_offset_src_dst;
 mask += thread_offset_mask;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

13 changes: 8 additions & 5 deletions
transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;
 int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

4 changes: 4 additions & 0 deletions
transformer_engine/pytorch/csrc/extensions.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
 (input.scalar_type() == at::ScalarType::BFloat16),
 "Only fp16 and bf16 are supported");
 AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
 if (!input.is_contiguous())
 input = input.contiguous();
 if (!mask.is_contiguous())
 mask = mask.contiguous();

 const int batches = input.size(0);
 const int pad_batches = mask.size(0);
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
}
}
if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
if (regex.test(text)) {
found = true;
var frag = document.createDocumentFragment();
var parts = text.split(regex);
parts.forEach(function(part, i) {
if (i % 2 === 0) {
frag.appendChild(document.createTextNode(part));
} else {
var span = document.createElement('span');
span.className = 'userscript-highlight';
span.textContent = part;
frag.appendChild(span);
}
});
node.parentNode.replaceChild(frag, node);
}
});
} else if (node.nodeType === 1 && node.childNodes) { // element
var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];
if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
}
}
}
highlight(document.body);
// Re-highlight on dynamic content
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Fix the integer overflow in fused softmax by ptrendx · Pull Request #60 · NVIDIA/TransformerEngine · GitHub
Skip to content
Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

ptrendx
merged 1 commit into

from

Jan 27, 2023
 Merged


Fix the integer overflow in fused softmax
#60
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


29 changes: 17 additions & 12 deletions
transformer_engine/common/fused_softmax/scaled_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 int pad_first_batch = 0;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t pad_first_batch = 0;
 if (pad_batches != 1) { // bert style
 pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
 * WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset_src_dst;
 dst += thread_offset_src_dst;
 mask += thread_offset_mask;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

13 changes: 8 additions & 5 deletions
transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;
 int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

4 changes: 4 additions & 0 deletions
transformer_engine/pytorch/csrc/extensions.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
 (input.scalar_type() == at::ScalarType::BFloat16),
 "Only fp16 and bf16 are supported");
 AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
 if (!input.is_contiguous())
 input = input.contiguous();
 if (!mask.is_contiguous())
 mask = mask.contiguous();

 const int batches = input.size(0);
 const int pad_batches = mask.size(0);
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
Fix the integer overflow in fused softmax by ptrendx · Pull Request #60 · NVIDIA/TransformerEngine · GitHub
Skip to content
Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

ptrendx
merged 1 commit into

from

Jan 27, 2023
 Merged


Fix the integer overflow in fused softmax
#60
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


29 changes: 17 additions & 12 deletions
transformer_engine/common/fused_softmax/scaled_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 int pad_first_batch = 0;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t pad_first_batch = 0;
 if (pad_batches != 1) { // bert style
 pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
 * WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset_src_dst;
 dst += thread_offset_src_dst;
 mask += thread_offset_mask;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

13 changes: 8 additions & 5 deletions
transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;
 int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

4 changes: 4 additions & 0 deletions
transformer_engine/pytorch/csrc/extensions.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
 (input.scalar_type() == at::ScalarType::BFloat16),
 "Only fp16 and bf16 are supported");
 AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
 if (!input.is_contiguous())
 input = input.contiguous();
 if (!mask.is_contiguous())
 mask = mask.contiguous();

 const int batches = input.size(0);
 const int pad_batches = mask.size(0);
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Fix the integer overflow in fused softmax by ptrendx · Pull Request #60 · NVIDIA/TransformerEngine · GitHub
Skip to content
Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

ptrendx
merged 1 commit into

from

Jan 27, 2023
 Merged


Fix the integer overflow in fused softmax
#60
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


29 changes: 17 additions & 12 deletions
transformer_engine/common/fused_softmax/scaled_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 int pad_first_batch = 0;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t pad_first_batch = 0;
 if (pad_batches != 1) { // bert style
 pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
 * WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset_src_dst;
 dst += thread_offset_src_dst;
 mask += thread_offset_mask;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

13 changes: 8 additions & 5 deletions
transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;
 int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

4 changes: 4 additions & 0 deletions
transformer_engine/pytorch/csrc/extensions.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
 (input.scalar_type() == at::ScalarType::BFloat16),
 "Only fp16 and bf16 are supported");
 AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
 if (!input.is_contiguous())
 input = input.contiguous();
 if (!mask.is_contiguous())
 mask = mask.contiguous();

 const int batches = input.size(0);
 const int pad_batches = mask.size(0);
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Fix the integer overflow in fused softmax by ptrendx · Pull Request #60 · NVIDIA/TransformerEngine · GitHub
Skip to content
Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

ptrendx
merged 1 commit into

from

Jan 27, 2023
 Merged


Fix the integer overflow in fused softmax
#60
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


29 changes: 17 additions & 12 deletions
transformer_engine/common/fused_softmax/scaled_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 int pad_first_batch = 0;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t pad_first_batch = 0;
 if (pad_batches != 1) { // bert style
 pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
 * WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset_src_dst;
 dst += thread_offset_src_dst;
 mask += thread_offset_mask;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

13 changes: 8 additions & 5 deletions
transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;
 int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

4 changes: 4 additions & 0 deletions
transformer_engine/pytorch/csrc/extensions.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
 (input.scalar_type() == at::ScalarType::BFloat16),
 "Only fp16 and bf16 are supported");
 AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
 if (!input.is_contiguous())
 input = input.contiguous();
 if (!mask.is_contiguous())
 mask = mask.contiguous();

 const int batches = input.size(0);
 const int pad_batches = mask.size(0);
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
Fix the integer overflow in fused softmax by ptrendx · Pull Request #60 · NVIDIA/TransformerEngine · GitHub
Skip to content
Fix the integer overflow in fused softmax#60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

ptrendx
merged 1 commit into

from

Jan 27, 2023
 Merged


Fix the integer overflow in fused softmax
#60
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

Jump to file


Failed to load files. 
Loading
 Diff view

 Diff view


29 changes: 17 additions & 12 deletions
transformer_engine/common/fused_softmax/scaled_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -121,8 +121,9 @@ __global__ void scaled_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -133,8 +134,9 @@ __global__ void scaled_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -236,9 +238,10 @@ __global__ void scaled_masked_softmax_warp_forward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
 int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 int pad_first_batch = 0;
 size_t first_batch = (blockDim.y * (blockIdx.x + gridDim.x *
 (blockIdx.y + gridDim.y * blockIdx.z))
 + threadIdx.y) * WARP_BATCH;
 size_t pad_first_batch = 0;
 if (pad_batches != 1) { // bert style
 pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y)
 * WARP_BATCH;
Expand All@@ -255,9 +258,11 @@ __global__ void scaled_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_src_dst = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset_mask = pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset_src_dst;
 dst += thread_offset_src_dst;
 mask += thread_offset_mask;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -365,7 +370,7 @@ __global__ void scaled_masked_softmax_warp_backward(

 // blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
 // gridDim/blockIdx = (seq_len, attn_heads, batches)
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
size_t first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
 // many batches have to computed within this WARP.
Expand All@@ -377,7 +382,7 @@ __global__ void scaled_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

13 changes: 8 additions & 5 deletions
transformer_engine/common/fused_softmax/scaled_upper_triang_masked_softmax.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -139,7 +139,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;
 int warp_iteration_limit = (local_seq + ELEMENTS_PER_LDG_STG * WARP_SIZE - 1)/ WARP_SIZE;

Expand All@@ -152,8 +153,9 @@ __global__ void scaled_upper_triang_masked_softmax_warp_forward(
 // there might be multiple batches per warp. compute the index within the batch
 int local_idx = threadIdx.x;

 src += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 dst += first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 src += thread_offset;
 dst += thread_offset;

 // load data from global memory
 acc_t elements[WARP_BATCH][WARP_ITERATIONS];
Expand DownExpand Up@@ -263,7 +265,8 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
 constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;

 int first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH + blockIdx.x;
 size_t first_batch = (blockDim.y * blockIdx.y + threadIdx.y) * gridDim.x * WARP_BATCH
 + blockIdx.x;
 int local_seq = blockIdx.x + 1;

 // micro_batch_size might not be a multiple of WARP_BATCH. Check how
Expand All@@ -276,7 +279,7 @@ __global__ void scaled_upper_triang_masked_softmax_warp_backward(
 int local_idx = threadIdx.x;

 // the first element to process by the current thread
int thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
size_t thread_offset = first_batch * stride + ELEMENTS_PER_LDG_STG * local_idx;
 grad += thread_offset;
 output += thread_offset;
 gradInput += thread_offset;
Expand Down

4 changes: 4 additions & 0 deletions
transformer_engine/pytorch/csrc/extensions.cu

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -687,6 +687,10 @@ at::Tensor scaled_masked_softmax_forward(at::Tensor input,
 (input.scalar_type() == at::ScalarType::BFloat16),
 "Only fp16 and bf16 are supported");
 AT_ASSERTM(mask.dim() == 4, "expected 4D tensor");
 if (!input.is_contiguous())
 input = input.contiguous();
 if (!mask.is_contiguous())
 mask = mask.contiguous();

 const int batches = input.size(0);
 const int pad_batches = mask.size(0);
Expand Down