for the i-th GAS space, to control the number of allowed supergroups depending on the interspace excitations n exc . Table shows a steep scaling of the memory with n exc . Our GAS-PCHB implementation uses hybrid parallelization, and precomputes the probability distributions in shared memory on every node. Thus, in the case of the stack of five benzene molecules ≈ 35 GB per node are required for three interspace excitations (Table ). The memory demand would have been larger with pure message-passing parallelization, where each process requires its own copy of the probability distributions. In that scenario, a 40 processes node would require 1.5 TB of memory for the same system. Since drawing a number is a read-only operation, no complicated locking mechanisms or atomic operations are required, after the distributions have been initialized. The memory demand is further reduced by a factor of ≈ Moreover, as shown in the next section, in practical calculations double interspace excitations are usually enough to recover the Full CI energy for chemically motivated GAS constraints. If the number of interspace excitations is low, the memory demand remains contained and a larger number of particles and GAS subspaces are accessible. For example, in Table , we show the memory requirements for a hypothetical [n • (6, 6)] GAS calculation, with varying number of GAS subspaces, n, and using a fixed number of interspace excitations, n exc = 2. On today's scientific computing hardware, up to eight of such (6, 6) GAS subspaces can be correlated (≈ 1 TB). In this context, we note again that the number of supergroups is independent from the number of orbitals, and only depends on the number of GAS spaces and the level of interspace excitations.