GeezerVison is showing github.com — gh-124951: Optimize base64 encode & decode for an easy 2-3x speedup [no SIMD] by gpshead · Pull Request #143262 · python/cpython
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Dec 29, 2025
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Optimize base64 encoding/decoding by eliminating loop-carried dependencies. Key changes:
- Add
base64_encode_trio() and base64_decode_quad() helper functions that process complete groups independently
- Add
base64_encode_fast() and base64_decode_fast() wrappers
- Update
b2a_base64 and a2b_base64 to use fast path for complete groups
The binasciibench I used measuring base64 encoding/decoding throughput is included in commit history, but i pulled it out of the PR in favor of adding to pyperformance.
Performance gains (encode/decode speedup vs main, PGO builds):
64 bytes 64K 1M
Zen2: 1.2x/1.8x 1.7x/2.8x 1.5x/2.8x
Zen4: 1.2x/1.7x 1.6x/3.0x 1.5x/3.0x [old data, likely faster]
M4: 1.3x/1.9x 2.3x/2.8x 2.4x/2.9x [old data, likely faster]
RPi5-32: 1.2x/1.2x 2.4x/2.4x 2.0x/2.1x
RPi4-64: 1.3x/2.0x 2.4x/5.0x 1.8x/5.0x
Additional SIMD implementations (NEON, AVX-512 VBMI) can achieve +50% (M4) to +1500% (!! Zen4) further gains and are planned for follow-on work if deemed simple to maintain.
Widely used third party libraries contain industry canonical SIMD accelerated variants such as simdutf (C++ based unfortunately) so the decision of how to link and use those and when is best kept separate.
This PR's simple pure better use of modern CPU functional unit pipelining wins make sense regardless.
Based on my exploratory work done in main...gpshead:cpython:claude/vectorize-base64-c-S7Hku
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Add Tools/binasciibench/binasciibench.py benchmark for measuring base64
encoding/decoding throughput.
Optimize base64 encoding/decoding by eliminating loop-carried dependencies.
Key changes:
- Add base64_encode_trio() and base64_decode_quad() helper functions
that process complete groups independently
- Add base64_encode_fast() and base64_decode_fast() wrappers
- Update b2a_base64 and a2b_base64 to use fast path for complete groups
Performance gains (encode/decode speedup vs main, PGO builds):
64 bytes 64K 1M
Zen2: 1.1x/1.6x 1.6x/2.4x 1.4x/2.4x
Zen4: 1.2x/1.7x 1.6x/3.0x 1.5x/3.0x
M4: 1.3x/1.9x 2.3x/2.8x 2.4x/2.9x
RPi5-32: 1.4x/1.4x 2.4x/2.0x 2.0x/1.9x
Additional SIMD implementations (NEON, AVX-512 VBMI) can achieve
+50% to +1500% further gains and are planned for follow-on work.
Co-authored-by: Claude Opus 4.5 <[email protected]>
gpshead
changed the title
Optimize base64 encode and decode for an easy 2-3x performance win
gh-124951: Optimize base64 encode and decode for an easy 2-3x performance win [no SIMD required]
Dec 29, 2025
gpshead
changed the title
gh-124951: Optimize base64 encode and decode for an easy 2-3x performance win [no SIMD required]
gh-124951: Optimize base64 encode and decode for an easy 2-3x speedup [no SIMD required]
Dec 29, 2025
gpshead
changed the title
gh-124951: Optimize base64 encode and decode for an easy 2-3x speedup [no SIMD required]
gh-124951: Optimize base64 encode & decode for an easy 2-3x speedup [no SIMD]
Dec 29, 2025
MSVC doesn't support forward declarations of arrays without explicit
size. Move the table definition before the inline functions that use
it, eliminating the need for a forward declaration.
Co-authored-by: Claude Opus 4.5 <[email protected]>
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Add Py_ALIGNED(64) to both lookup tables to ensure each fits
within a single L1 cache line, reducing potential cache misses
during encoding/decoding loops.
Co-authored-by: Claude Opus 4.5 <[email protected]>
Replace hardcoded '=' characters with the BASE64_PAD macro
for consistency with the rest of the codebase.
Co-authored-by: Claude Opus 4.5 <[email protected]>
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Looks pretty simple with large benefit.
BTW, I'm going to add support for ignorechars in the decoder, so it could support a multiline input without ignoring all other errors. The decoder will return on the fast path for each line.
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Address review feedback from serhiy-storchaka: the fast path was doing
two checks per group - an explicit PAD comparison and the invalid char
check in base64_decode_quad().
Change PAD's table entry from 0 to 64 so the existing (v0|v1|v2|v3)&0xc0
check catches it, eliminating 4 comparisons per group.
The slow path is unaffected since it checks for PAD character before
the table lookup.
Decode is ~16% faster at 64K (1.62 GB/s → 1.88 GB/s).
Co-authored-by: Claude Opus 4.5 <[email protected]>
Suggested by serhiy-storchaka: replace index math (in + i*3, out + i*4)
with pointer increments. Encode is ~7% faster at 64K (2.11 → 2.25 GB/s).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <[email protected]>
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thunder-coding
pushed a commit
to thunder-coding/cpython
that referenced
this pull request
Feb 15, 2026
…edup [no SIMD] (pythonGH-143262)
Optimize base64 encoding/decoding by eliminating loop-carried dependencies. Key changes:
- Add `base64_encode_trio()` and `base64_decode_quad()` helper functions that process complete groups independently
- Add `base64_encode_fast()` and `base64_decode_fast()` wrappers
- Update `b2a_base64` and `a2b_base64` to use fast path for complete groups
Performance gains (encode/decode speedup vs main, PGO builds):
```
64 bytes 64K 1M
Zen2: 1.2x/1.8x 1.7x/2.8x 1.5x/2.8x
Zen4: 1.2x/1.7x 1.6x/3.0x 1.5x/3.0x [old data, likely faster]
M4: 1.3x/1.9x 2.3x/2.8x 2.4x/2.9x [old data, likely faster]
RPi5-32: 1.2x/1.2x 2.4x/2.4x 2.0x/2.1x
```
Based on my exploratory work done in python/cpython@main...gpshead:cpython:claude/vectorize-base64-c-S7Hku
See PR and issue for further thoughts on sometimes MUCH faster SIMD vectorized versions of this.
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