  We present ATC, a C++ library for advanced Tucker-based lossy compression of
dense multidimensional numerical data in a shared-memory parallel setting,
based on the sequentially truncated higher-order singular value decomposition
(ST-HOSVD) and bit plane truncation. Several techniques are proposed to improve
speed, memory usage, error control and compression rate. First, a hybrid
truncation scheme is described which combines Tucker rank truncation and
TTHRESH quantization [Ballester-Ripoll et al., IEEE Trans. Visual. Comput.
Graph., 2020]. We derive a novel expression to approximate the error of
truncated Tucker decompositions in the case of core and factor perturbations.
Furthermore, we parallelize the quantization and encoding scheme and adjust
this phase to improve error control. Moreover, implementation aspects are
described, such as an ST-HOSVD procedure using only a single transposition. We
also discuss several usability features of ATC, including the presence of
multiple interfaces, extensive data type support and integrated downsampling of
the decompressed data. Numerical results show that ATC maintains
state-of-the-art Tucker compression rates, while providing average speed-up
factors of 2.2-3.5 and halving memory usage. Furthermore, our compressor
provides precise error control, only deviating 1.4% from the requested error on
average. Finally, ATC often achieves higher compression than non-Tucker-based
compressors in the high-error domain.
