mirror of
https://github.com/ruvnet/RuVector.git
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9d79eedec9
Key optimizations in v0.1.31: - W2 matrix stored transposed for contiguous row access during sparse accumulation - SIMD GELU/SiLU using AVX2+FMA polynomial approximations - Cached SIMD feature detection with OnceLock (eliminates runtime CPUID calls) - SIMD axpy for vectorized weight accumulation Benchmark results (512 input, 2048 hidden): - 10% active: 130µs (83% reduction, 52× vs dense) - 30% active: 383µs (83% reduction, 18× vs dense) - 50% active: 651µs (83% reduction, 10× vs dense) - 70% active: 912µs (83% reduction, 7× vs dense) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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376 B
JSON
22 lines
No EOL
376 B
JSON
{
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"name": "@ruvector/attention-linux-x64-gnu",
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"version": "0.1.4",
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"os": [
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"linux"
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],
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"cpu": [
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"x64"
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],
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"main": "attention.linux-x64-gnu.node",
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"files": [
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"attention.linux-x64-gnu.node"
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],
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"license": "MIT OR Apache-2.0",
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"engines": {
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"node": ">= 10"
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},
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"libc": [
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"glibc"
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],
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"repository": "https://github.com/ruvnet/ruvector"
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} |