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[Performance][PD Disaggregation] optimize TokenToKVPoolAllocator by sorting free pages #8133
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -51,23 +51,24 @@ def __init__( | |
| self._kvcache = kvcache | ||
|
|
||
| self.free_pages = None | ||
| self.release_pages = None | ||
| self.is_not_in_free_group = True | ||
| self.free_group = [] | ||
|
|
||
| def debug_print(self) -> str: | ||
| return "" | ||
|
|
||
| def available_size(self): | ||
| return len(self.free_pages) * self.page_size | ||
| return (len(self.free_pages) + len(self.release_pages)) * self.page_size | ||
|
|
||
| def get_kvcache(self): | ||
| return self._kvcache | ||
|
|
||
| def restore_state(self, free_pages): | ||
| self.free_pages = free_pages | ||
| def restore_state(self, state): | ||
| self.free_pages, self.release_pages = state | ||
|
|
||
| def backup_state(self): | ||
| return self.free_pages | ||
| return (self.free_pages, self.release_pages) | ||
|
|
||
| def free_group_begin(self): | ||
| self.is_not_in_free_group = False | ||
|
|
@@ -78,6 +79,14 @@ def free_group_end(self): | |
| if self.free_group: | ||
| self.free(torch.cat(self.free_group)) | ||
|
|
||
| def merge_and_sort_free(self): | ||
| if len(self.release_pages) > 0: | ||
| self.free_pages = torch.cat((self.free_pages, self.release_pages)) | ||
| self.free_pages, _ = torch.sort(self.free_pages) | ||
| self.release_pages = torch.empty( | ||
| (0,), dtype=self.release_pages.dtype, device=self.device | ||
| ) | ||
|
|
||
| def get_cpu_copy(self, *args, **kwargs): | ||
| # FIXME: reuse the get_cpu_copy after paged allocator is implemented | ||
| raise NotImplementedError() | ||
|
|
@@ -119,12 +128,15 @@ def clear(self): | |
| ) | ||
| self.is_not_in_free_group = True | ||
| self.free_group = [] | ||
| self.release_pages = torch.empty((0,), dtype=torch.int64, device=self.device) | ||
|
|
||
| def available_size(self): | ||
| # To avoid minor "len(free_pages) * 1" overhead | ||
| return len(self.free_pages) | ||
| return len(self.free_pages) + len(self.release_pages) | ||
|
|
||
| def alloc(self, need_size: int): | ||
| if need_size > len(self.free_pages): | ||
| self.merge_and_sort_free() | ||
| if need_size > len(self.free_pages): | ||
| return None | ||
|
|
||
|
|
@@ -137,7 +149,7 @@ def free(self, free_index: torch.Tensor): | |
| return | ||
|
|
||
| if self.is_not_in_free_group: | ||
| self.free_pages = torch.cat((self.free_pages, free_index)) | ||
| self.release_pages = torch.cat((self.release_pages, free_index)) | ||
| else: | ||
| self.free_group.append(free_index) | ||
|
|
||
|
|
@@ -421,6 +433,8 @@ def alloc(self, need_size: int): | |
| ), "The allocation size should be page-aligned" | ||
|
|
||
| num_pages = need_size // self.page_size | ||
| if num_pages > len(self.free_pages): | ||
| self.merge_and_sort_free() | ||
| if num_pages > len(self.free_pages): | ||
| return None | ||
|
|
||
|
|
@@ -446,6 +460,17 @@ def alloc_extend( | |
| (last_loc + 1) % self.page_size == prefix_lens % self.page_size | ||
| ) | ||
|
|
||
| estimated_num_new_pages = ( | ||
| ( | ||
| (seq_lens + self.page_size - 1) // self.page_size | ||
| - (prefix_lens + self.page_size - 1) // self.page_size | ||
| ) | ||
| .sum() | ||
| .item() | ||
|
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Is it possible to reduce the sync by estimating with
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I've just changed this logic by using extend_num_tokens |
||
| ) | ||
| if estimated_num_new_pages > len(self.free_pages): | ||
| self.merge_and_sort_free() | ||
|
|
||
| bs = len(prefix_lens) | ||
| out_indices = torch.empty( | ||
| (extend_num_tokens,), dtype=torch.int64, device=self.device | ||
|
|
@@ -483,6 +508,17 @@ def alloc_decode( | |
| (last_loc + 2) % self.page_size == seq_lens % self.page_size | ||
| ) | ||
|
|
||
| estimated_num_new_pages = ( | ||
| ( | ||
| (seq_lens + self.page_size - 1) // self.page_size | ||
| - (seq_lens - 1 + self.page_size - 1) // self.page_size | ||
| ) | ||
| .sum() | ||
| .item() | ||
| ) | ||
| if estimated_num_new_pages > len(self.free_pages): | ||
| self.merge_and_sort_free() | ||
|
|
||
| bs = len(seq_lens) | ||
| out_indices = torch.empty((bs,), dtype=torch.int64, device=self.device) | ||
| alloc_decode_kernel[(bs,)]( | ||
|
|
@@ -511,7 +547,7 @@ def free(self, free_index: torch.Tensor): | |
|
|
||
| if self.is_not_in_free_group: | ||
| free_page_indices = torch.unique(free_index // self.page_size) | ||
| self.free_pages = torch.cat((free_page_indices, self.free_pages)) | ||
| self.release_pages = torch.cat((free_page_indices, self.release_pages)) | ||
| else: | ||
| self.free_group.append(free_index) | ||
|
|
||
|
|
@@ -525,6 +561,7 @@ def clear(self): | |
| ) | ||
| self.is_not_in_free_group = True | ||
| self.free_group = [] | ||
| self.release_pages = torch.empty((0,), dtype=torch.int64, device=self.device) | ||
|
|
||
| def get_cpu_copy(self, indices): | ||
| return self._kvcache.get_cpu_copy(indices) | ||
|
|
@@ -633,6 +670,17 @@ def alloc_extend( | |
| (last_loc + 1) % self.page_size == prefix_lens % self.page_size | ||
| ) | ||
|
|
||
| estimated_num_new_pages = ( | ||
| ( | ||
| (seq_lens + self.page_size - 1) // self.page_size | ||
| - (prefix_lens + self.page_size - 1) // self.page_size | ||
| ) | ||
| .sum() | ||
| .item() | ||
| ) | ||
| if estimated_num_new_pages > len(self.free_pages): | ||
| self.merge_and_sort_free() | ||
|
|
||
| bs = len(prefix_lens) | ||
| out_indices = torch.empty( | ||
| (extend_num_tokens,), dtype=torch.int32, device=self.device | ||
|
|
@@ -668,6 +716,17 @@ def alloc_decode( | |
| (last_loc + 2) % self.page_size == seq_lens % self.page_size | ||
| ) | ||
|
|
||
| estimated_num_new_pages = ( | ||
| ( | ||
| (seq_lens + self.page_size - 1) // self.page_size | ||
| - (seq_lens - 1 + self.page_size - 1) // self.page_size | ||
| ) | ||
| .sum() | ||
| .item() | ||
| ) | ||
| if estimated_num_new_pages > len(self.free_pages): | ||
| self.merge_and_sort_free() | ||
|
|
||
| bs = len(seq_lens) | ||
| out_indices = torch.empty((bs,), dtype=torch.int32, device=self.device) | ||
|
|
||
|
|
@@ -692,3 +751,4 @@ def alloc_decode( | |
| def clear(self): | ||
| super().clear() | ||
| self.free_pages = self.free_pages.to(torch.int32) | ||
| self.release_pages = self.release_pages.to(torch.int32) | ||
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This code has been duplicated too many times. Please write a common subfunction for it.
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Thanks for your comment, I'll fix it soon.