  The Bluebild algorithm is a new technique for image synthesis in radio
astronomy which forms a least-squares estimate of the sky intensity function
using the theory of sampling and interpolation operators. We present an HPC
implementation of the Bluebild algorithm for radio-interferometric imaging:
Bluebild Imaging++ (BIPP). BIPP is a spherical imager that leverages functional
PCA to decompose the sky into distinct energy levels. The library features
interfaces to C++, C and Python and is designed with seamless GPU acceleration
in mind. We evaluate the accuracy and performance of BIPP on simulated
observations of the upcoming Square Kilometer Array Observatory and real data
from the Low-Frequency Array (LOFAR) telescope. We find that BIPP offers
accurate wide-field imaging with no need for a w-term approximation and has
improved execution time with respect to the interferometric imaging libraries
CASA and WSClean. Futhermore, due to the energy level decomposition, images
produced with BIPP can reveal information about faint and diffuse structures
before any cleaning iterations. The source code of BIPP is publicly released.
