Optimize spmatrix._set_many #7888
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
emcastillo
added
cat:performance
|
@emcastillo how does this CI work? Are the tests actually running, or do they not start until triggered by something? |
|
CIs are triggered after review by one of the maintainers |
emcastillo
reviewed
Oct 2, 2023
| mask = offsets > -1 | ||
| self.data[offsets[mask]] = x[mask] | ||
|
|
||
| if mask.all(): |
There was a problem hiding this comment.
This is still doing device synchronization since you need to bring back the value to the host for the if comparisson, so I think that execution time won't benefit from these changes
|
Thanks a lot for the PR! Sorry, can you try to benchmark the code using this? https://docs.cupy.dev/en/stable/user_guide/performance.html I am interested in seeing the GPU performance. Thanks |
|
@emcastillo thanks for the comments. I understand that there will still be a synchronization because of the Test function (run on Google Colab with T4 GPU)import numpy as np
import cupy
import cupyx
def benchmark_update_only(size, nnz):
rows = cupy.random.randint(0, size, nnz)
cols = cupy.random.randint(0, size, nnz)
old_vals = cupy.random.random(nnz)
new_vals = cupy.random.random(nnz)
mat_cupy_old = cupyx.scipy.sparse.csr_matrix((old_vals, (rows, cols)))
mat_cupy_new = cupyx.scipy.sparse.csr_matrix((old_vals, (rows, cols)))
def run_old():
vals = cupy.roll(new_vals, -1)
mat_cupy_old._set_many(rows, cols, vals)
return mat_cupy_old.get()
def run_new():
# _set_many() uses mask.all()
vals = cupy.roll(new_vals, -1)
_set_many(mat_cupy_new, rows, cols, vals)
return mat_cupy_new.get()
print(f"{size = }, {nnz = }")
print("Old _set_many:")
print(cupyx.profiler.benchmark(run_old, (), n_repeat=100))
print("New _set_many:")
print(cupyx.profiler.benchmark(run_new, (), n_repeat=100))
mat_scipy_old = run_old()
mat_scipy_new = run_new()
assert np.array_equal(mat_scipy_old.indices, mat_scipy_new.indices)
assert np.array_equal(mat_scipy_old.indptr, mat_scipy_new.indptr)
assert np.allclose(mat_scipy_old.data, mat_scipy_new.data)
return mat_scipy_old, mat_scipy_newResults: |
|
Seems a significant improvement, let me kick the CIs |
|
/test mini |
|
Actually, this looks to be just as fast as using Note the only change from def _set_many(self, i, j, x):
"""Sets value at each (i, j) to x
Here (i,j) index major and minor respectively, and must not contain
duplicate entries.
"""
i, j, M, N = self._prepare_indices(i, j)
x = cupy.array(x, dtype=self.dtype, copy=True, ndmin=1).ravel()
new_sp = cupyx.scipy.sparse.csr_matrix(
(cupy.arange(self.nnz, dtype=cupy.float32),
self.indices, self.indptr), shape=(M, N))
offsets = new_sp._get_arrayXarray(
i, j, not_found_val=-1).astype(cupy.int32).ravel()
if -1 not in offsets.get(): # This is the only line that is different from main
# only affects existing non-zero cells
self.data[offsets] = x
return
mask = offsets > -1
self.data[offsets[mask]] = x[mask]
# only insertions remain
warnings.warn('Changing the sparsity structure of a '
'{}_matrix is expensive.'.format(self.format),
_base.SparseEfficiencyWarning)
mask = ~mask
i = i[mask]
i[i < 0] += M
j = j[mask]
j[j < 0] += N
self._insert_many(i, j, x[mask])Benchmark: |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR implements the change proposed in #7876.
Performance tests
Run with CuPy 11.0.0 on Google Colab because I don't have a local GPU.
Update only, no insert
Results:
Insert only, no update
I expect very little performance difference here because this line
cupy/cupyx/scipy/sparse/_compressed.py
Line 540 in 5c32e40
Results. Old and new are the same within the noise/reproducibility of the test.