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GPU-accelerated coordinate projection library

Project description

vibeProj

GPU-accelerated coordinate projection library. Extracted from RAPIDS cuProj, re-engineered as a pure Python + CuPy package, and expanded from 1 to 20 projections — each with a fused NVRTC kernel that runs the full transform pipeline in a single GPU kernel launch.

[!WARNING] vibeProj is very early in development. Operations may be unoptimized or have multiple Host/Device transfers causing reduced performance. File an issue if you hit a problem!

Performance

On an RTX 4090 vs i9-13900k, 1M coordinates: (Note: datacenter GPUs will see far higher speedups due to better double precision performance)

Projection GPU vs CPU
Transverse Mercator / UTM 0.50 ms 260x
Lambert Conformal Conic 0.54 ms 82x
Albers Equal Area 0.28 ms 114x
Web Mercator 0.15 ms 95x
Equal Earth 0.21 ms 139x
Plate Carrée 0.04 ms 169x

All 20 projections run sub-millisecond at 1M coordinates. See full benchmark in the repo.

Supported Projections

Projection Internal Name EPSG Examples
Transverse Mercator / UTM tmerc 32601–32760, 27700
Web Mercator webmerc 3857
Mercator (ellipsoidal) merc 3395
Lambert Conformal Conic lcc 2154
Albers Equal Area aea 5070
Polar Stereographic stere 3031, 3413
Lambert Azimuthal Equal Area laea 3035
Oblique Stereographic sterea 28992
Plate Carrée eqc 4087
Sinusoidal sinu
Equal Earth eqearth 8857
Cylindrical Equal Area cea 6933
Orthographic ortho
Gnomonic gnom
Mollweide moll
Robinson robin
Winkel Tripel wintri
Natural Earth natearth
Azimuthal Equidistant aeqd
Geostationary Satellite geos

Install

pip install vibeproj          # CPU-only (NumPy fallback)
pip install vibeproj[gpu]     # with CuPy for GPU acceleration

For development:

uv sync               # CPU-only
uv sync --group gpu   # with CuPy

Usage

from vibeproj import Transformer

# Default: native CRS axis order (matches pyproj)
t = Transformer.from_crs("EPSG:4326", "EPSG:32631")
x, y = t.transform(49.0, 2.0)           # (lat, lon) in, (easting, northing) out

# always_xy=True: (lon, lat) order — matches shapely/geopandas
t = Transformer.from_crs("EPSG:4326", "EPSG:32631", always_xy=True)
x, y = t.transform(2.0, 49.0)           # (lon, lat) in, (easting, northing) out

vibeSpatial Integration (zero-copy GPU)

# Pre-allocated output, no intermediate allocations, stays on GPU
t = Transformer.from_crs(src_crs, dst_crs, always_xy=True)
new_x = cp.empty_like(buf.x)
new_y = cp.empty_like(buf.y)
t.transform_buffers(buf.x, buf.y, out_x=new_x, out_y=new_y)

transform_buffers() accepts pre-allocated CuPy output arrays, writes results directly into them, and returns the same objects. No host round-trip, no intermediate allocation. Designed for vibeSpatial's OwnedGeometryArray coordinate buffers.

Architecture

  • Pure Python + CuPy — no compiled extensions, no CMake
  • Fused NVRTC kernels — each projection's full pipeline (axis swap, deg/rad, central meridian, projection math, scale/offset) runs in a single CUDA kernel launch via CuPy RawKernel
  • NumPy fallback — all projections work on CPU when CuPy is unavailable
  • pyproj for CRS metadata — EPSG codes resolved via pyproj, transform math is ours
  • fp64 I/O — input/output arrays always double precision (ADR-0002 compliant)
  • Auto GPU detection — queries SingleToDoublePrecisionPerfRatio to classify consumer vs datacenter GPU

Test

uv run pytest                    # all tests (85 total)
uv run pytest tests/test_fused_kernels.py  # GPU kernel tests (requires CuPy)

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