is paradigm shi was named the memory wall. Moore's law is de nitely near the end of its life. e traditional sequential algorithms of quantum chemistry are currently being redesigned and replaced by parallel equivalents by multiple groups around the world. is has obviously a signi cant in uence on methodological developments. e most iconic example of this move towards parallel-friendly methods is the recently developed full con guration interaction quantum Monte Carlo (FCIQMC) method by Alavi and coworkers. FCIQMC can be interpreted as a Monte Carlo equivalent of older selected con guration interaction (sCI) algorithms such as CIPSI (Con guration Interaction using a Perturbative Selection made Iteratively), that are iterative and thus a priori not well adapted to massively parallel architecture. As we shall see here, things turn out di erently, and the focus of the present article is to show that sCI methods can be made e cient on modern massively parallel supercomputers. P is an open-source suite of wave function quantum chemistry methods mainly developed at the Laboratoire de Chimie et Physique antiques (LCPQ) in Toulouse (France), and the Laboratoire de Chimie éorique (LCT) in Paris. Its source code is freely available on GitHub at the following address: h ps://github.com/ antumPackage/qp2. P strives to allow easy implementation and experimentation of new methods, while making parallel computation as simple and e cient as possible. Accordingly, the initial choice of P was to go towards determinant-driven algorithms. Assuming a wave function expressed as a linear combination of determinants, a determinant-driven algorithm essentially implies that the outermost loop runs over determinants. On the other hand, more traditional integral-driven algorithms have their outermost loop running on the two-electron integrals appearing in the expression of the matrix elements in the determinant basis (see Sec. II B). Determinant-driven algorithms allow more exibility than their integral-driven counterparts, but they have been known for years to be less e cient than their integraldriven variant for solving electronic structure problems. In high-precision calculations, the number of determinants is larger than the number of integrals, justifying the integraldriven choice. However, today's programming standards impose parallelism, and if determinant-driven calculations prove to be be er adapted to parallelism, such methods could regain popularity. More conventional approaches have also been very successfully parallelized: CCSD(T), DMRG, GW, QMC, and many others. P was used in numerous applications, in particular to obtain reference ground-state energies as well as excitation energies for atomic and molecular systems. For example, in Ref. 44, P has been used to compute more than hundred very accurate transition energies for states of various characters (valence, Rydberg, n → π * , π → π * , singlet, triplet, . . . ) in 18 small molecules.