v2.9.1

2.9.1 (2024-02-27)

Fix

• Explicit narrowing conversions (25436ae)
• Match enum values between C and C# (4a69086)
• Recovering quantization settings in load (fd53619), closes #353 #343
• wildcard ES module imports (#351) (d5091ac), closes #351

Improve

• Report missing arguments in debug builds (ce5bbaf)
• Test reopening index (24be07b)

Make

• Clean-up the C# dir (70d646c)
• invalid C++17 Clang arg (23684aa)

Hashes

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v2.9.0

2.9.0 (2024-02-22)

Add

• SQLite binding (222de55)
• String distances to SQLite (ae4d0f0)

Docs

• Header refreshed (7465c29)
• Py and SQLite extensions (550624b)
• README.md link to Joins (#327) (1279c54), closes #327

Fix

• bug reports were immediately marked invalid (c5fc825)
• Error handling, mem safety bugs #335 (#339) (4747ef4), closes #335 #339
• Passing SQLite tests (6334983)
• Reported number of levels (9b1a06a)
• Skip non-Linux SQLite tests (b02d262)
• SQLite cosine function + tests (55464fb)
• undefined var error in remove api (8d86a9e)

Improve

• Multi property lookup (e8bf02c)
• Support multi-column vectors (66f1716)

Make

• npi ci (#330) (5680920), closes #330
• Add 3.12 wheels (d66f697)
• Change include paths (21db294)
• invalid C++17 Clang arg (2a6d779)
• Link libpthread for older Linux GCC builds (#324) (6f1e5dd), closes #324
• Parallel CI for Python wheels (a9ad89e)
• Upgrade SimSIMD & StringZilla (5481bdf)

Revert

• Postpone Apache Arrow integration (5d040ca)

Hashes

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v2.8.16

2.8.16 (2024-01-24)

Docs

• Downloads numbers (13cc624)

Fix

• SimSIMD dispatch (c8dc3b7), closes #320

Make

• Fix Node version for SemVer (a68fca6)
• Upgrade dependencies (6ab2150)
• Upgrade Node environment (f5b6750)

v2.8.15

2.8.15 (2024-01-09)

Fix

• exporting quantization enums in Go (#336) (93c74c3), closes #336

Hashes

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Faster Double-Precision Math

As was discussed in the SciPy integration thread, Python libraries use double-precision floating-point numbers by default.
So, in this release, I've extended the spatial distance functions in the underlying SimSIMD - Cos, L2sq, IP with support for double arguments with specialized implementations on AVX-512-capable x86 CPUs and SVE-capable Arm CPUs.

Benchmarking SimSIMD vs. SciPy on Intel Sapphire Rapids CPU

• Vector dimensions: 1536
• Vectors count: 1000
• Hardware capabilities: serial, x86_avx2, x86_avx512, x86_avx2fp16, x86_avx512fp16, x86_avx512vpopcntdq, x86_avx512vnni
• NumPy BLAS dependency: openblas64
• NumPy LAPACK dependency: dep140640983012528

Between 2 Vectors, Batch Size: 1

Datatype	Method	Ops/s	SimSIMD Ops/s	SimSIMD Improvement
f64	scipy.cosine	63,612	572,605	9.00 x
f64	scipy.sqeuclidean	238,547	915,596	3.84 x
f64	numpy.inner	449,499	986,522	2.19 x

Between 2 Vectors, Batch Size: 1,000

Datatype	Method	Ops/s	SimSIMD Ops/s	SimSIMD Improvement
f64	scipy.cosine	68,962	1,457,172	21.13 x
f64	scipy.sqeuclidean	247,727	1,535,547	6.20 x
f64	numpy.inner	463,509	1,512,004	3.26 x

Benchmarking SimSIMD vs. SciPy on AWS Graviton 3

• Vector dimensions: 1536
• Vectors count: 1000
• Hardware capabilities: serial, arm_neon, arm_sve
• NumPy BLAS dependency: openblas64
• NumPy LAPACK dependency: openblas64

Between 2 Vectors, Batch Size: 1

Datatype	Method	Ops/s	SimSIMD Ops/s	SimSIMD Improvement
f64	scipy.cosine	40,729	725,382	17.81 x
f64	scipy.sqeuclidean	160,812	728,114	4.53 x
f64	numpy.inner	473,443	767,374	1.62 x
f64	scipy.jensenshannon	15,684	38,528	2.46 x
f64	scipy.kl_div	49,983	61,811	1.24 x

Between 2 Vectors, Batch Size: 1,000

Datatype	Method	Ops/s	SimSIMD Ops/s	SimSIMD Improvement
f64	scipy.cosine	41,130	1,460,850	35.52 x
f64	scipy.sqeuclidean	162,147	1,486,255	9.17 x
f64	numpy.inner	473,856	1,580,136	3.33 x

Hashes

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v2.8.13

2.8.13 (2023-11-18)

Docs

• badges, comparisons with clustering tools (05b3109)

Improve

• Faster exports for non-multi Indexes (48655a3)

Hashes

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v2.8.12

2.8.12 (2023-11-13)

Docs

• Typo in Java README (#307) (494b9f0), closes #307
• Update Java's step-by-step build instructions (#306) (63d8027), closes #306

Fix

• Dumping to uninitialized memory in Java (9eaa10d)
• Key type mismatch in Java (25dc6fc)
• Normalize bit-vector length for SimSIMD (#311) (8a77b3e), closes #311
• OOM error in Java (2589979), closes #308

Improve

• TypeScript annotations (#309) (6a5e009), closes #309

Make

• Trace used compiler (7d17eab)

Hashes

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v2.8.11

2.8.11 (2023-11-11)

Fix

• loading of native libs from Jar with NativeUtils.java (#305) (40bb2fb), closes #305

v2.8.10

2.8.10 (2023-11-11)

Docs

• Reorganized sections (7431f94)

Fix

• Detecting GCC and forwarding Py settings (28cd82c)

Hashes

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v2.8.9

2.8.9 (2023-11-09)

Docs

• Compiling NodeJS bindings on Lambdas (aeb3956)

Fix

• Unpacking JS batch requests (b761680), closes #303

Make

• Upgrade SimSIMD (39a926e)

test

• usearch-js expected results (cf1b58f)

Hashes

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• usearch-v2.8.9.tar.gz : 1d337693896851554962f3ea89350ea82c5b13cbdb0357777b50d9e1688d6a02
• usearch-v2.8.9.zip : 39ca7284549ec55802fc6b55c9c90f011b074daaca38cccf67a9073aab4de02d
• usearch_linux_amd_2.8.9.deb : a017e3150cdacb1b8c3fea93bfb17fe5e8d3ef79f48d8422e2ac04386a3376b5
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• usearch_macOS_arm64_2.8.9.zip : 4fef6c22aebf39452f3569ea0aa7e4e76261ec91e10c02816b2b59652b23b8e2
• usearch_macOS_x86_64_2.8.9.zip : a7c969fa74e6f396995aafe16bc84184b5c62525f3d2c054f634844a09c5ca7a
• usearch_wasm_linux_arm64_2.8.9.tar.gz : 3e56e757c9b2260dff1ba2acfdb4966cd7c84ad560f65f57429375eb75c3ce1c
• usearch_wasm_linux_x86_64_2.8.9.tar.gz : 0fd3e878f47e7f9cc1a956631e1fe97ddfc2da44dc2a7d48695311cf0d77883c
• usearch_wasm_macos_arm64_2.8.9.zip : 6497cd781c47f03ecc7855eeac013fb8a6dc77f338cf6fd60bb61572ced1090f
• usearch_wasm_macos_x86_64_2.8.9.zip : 74fa03be9236dfbe394761eee3f02c0f99bcecd14115fa53a41be1157cf8bb92
• usearch_wasm_windows_x64_2.8.9.tar.gz : cacf78f4503e1463335ec67a4e8fff59b83a92e8d8128340e1e3b73802eaabc7
• usearch_wasm_windows_x86_2.8.9.tar.gz : dd6dba98a55c5da625dca96d32439c77a01f48bc68718db5c70b38d4b83747b9
• usearch_windows_x64_2.8.9.tar : 5e77f60ceb7e717ede45c7e79d40280b1be83d61b126fe74b1d97a91148c2a1a
• usearch_windows_x86_2.8.9.tar : 5e77f60ceb7e717ede45c7e79d40280b1be83d61b126fe74b1d97a91148c2a1a