Update master to 0.4.0 #219
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
Currently SIMD (SSE or AVX) is used for the cases when dimension is multiple of 4 or 16, when dimension size is not strictly equal to multiple of 4 or 16 a slower non-vectorized method is used. To improve performance for these cases new methods are added: `L2SqrSIMD(4|16)ExtResidual` - relies on existing `L2SqrSIMD(4|16)Ext` to compute up to *4 and *16 dimensions and finishes residual computation by method `L2Sqr`. Performance improvement compared to baseline is x3-4 times depending on dimension. Benchmark results: Run on (4 X 3300 MHz CPU s) CPU Caches: L1 Data 32 KiB (x2) L1 Instruction 32 KiB (x2) L2 Unified 256 KiB (x2) L3 Unified 4096 KiB (x1) Load Average: 2.18, 2.35, 3.88 ----------------------------------------------------------- Benchmark Time CPU Iterations ----------------------------------------------------------- TstDim65 14.7 ns 14.7 ns 20 * 47128209 RefDim65 50.2 ns 50.1 ns 20 * 10373751 TstDim101 24.7 ns 24.7 ns 20 * 28064436 RefDim101 90.4 ns 90.2 ns 20 * 7592191 TstDim129 31.4 ns 31.3 ns 20 * 22397921 RefDim129 125 ns 124 ns 20 * 5548862 TstDim257 59.3 ns 59.2 ns 20 * 10856753 RefDim257 266 ns 266 ns 20 * 2630926
…d 16 Currently SIMD (SSE or AVX) is used for the cases when dimension is multiple of 4 or 16, when dimension size is not strictly equal to multiple of 4 or 16 a slower non-vectorized method is used. To improve performnance for these cases new methods are added: `InnerProductSIMD(4|16)ExtResidual` - relies on existing `InnerProductSIMD(4|16)Ext` to compute up to *4 and *16 dimensions and finishes residual computation by non-vectorized method `InnerProduct`. Performance improvement compared to baseline is x3-4 times depending on dimension. Benchmark results: Run on (4 X 3300 MHz CPU s) CPU Caches: L1 Data 32 KiB (x2) L1 Instruction 32 KiB (x2) L2 Unified 256 KiB (x2) L3 Unified 4096 KiB (x1) Load Average: 2.10, 2.25, 2.46 ---------------------------------------------------------- Benchmark Time CPU Iterations ---------------------------------------------------------- TstDim65 14.0 ns 14.0 ns 20 * 48676012 RefDim65 50.3 ns 50.2 ns 20 * 12907985 TstDim101 23.8 ns 23.8 ns 20 * 27976276 RefDim101 91.4 ns 91.3 ns 20 * 7364003 TetDim129 30.0 ns 30.0 ns 20 * 23413955 RefDim129 123 ns 123 ns 20 * 5656383 TstDim257 57.8 ns 57.7 ns 20 * 11263073 RefDim257 268 ns 267 ns 20 * 2617478
Perf improvement for dimension not of factor 4 and 16
[MRG] Correct typo
Algorithm to perform dynamic/incremental updates of feature vectors
Fixed a typo in bindings.cpp
sjwsl
pushed a commit
to sjwsl/hnswlib
that referenced
this pull request
May 6, 2021
Update master to 0.4.0
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.
No description provided.