The celebrated asynchronous computability theorem (ACT) characterizes tasks solvable in the read-write shared-memory model using the unbounded full-information protocol, where in every round of computation, each process shares its complete knowledge of the system with the other processes. Therefore, ACT assumes shared-memory variables of unbounded capacity. It has been recently shown that boundedvariables can achieve the same computational power at the expense of extra rounds. However, the exact relationship between the bit capacity of the shared memory and the number of rounds required in order to implement one round of the full-information protocol remained unknown. In this paper, we focus on the asymptotic round complexity of bounded iterated shared-memory algorithms that simulate, up to isomorphism, the unbounded full-information protocol. We relate the round complexity to the number of processes $n$, the number of iterations of the full information protocol $r$, and the bit size per shared-memory entry $b$. By analyzing the corresponding protocol complex, a combinatorial structure representing reachable states, we derive necessary conditions and present a bounded full-information algorithm tailored to the bits available $b$ per shared memory entry. We show that for $n>2$, the round complexity required to implement the full-information protocol satisfies $Ω((n!)^{r-1} \cdot 2^{n-b})$. Our results apply to a range of iterated shared-memory models, from regular read-write registers to atomic and immediate snapshots. Moreover, our bounded full-information algorithm is asymptotically optimal for the iterated collect model and within a linear factor $n$ of optimal for the snapshot-based models.