The partitioned global address space (PGAS) model is popular for applying a classic shared memory approach to large systems, but some classes of problems rely on large numbers of small remote memory accesses targeting random locations across the network. On modern interconnects this can overwhelm the network, leading to message rate inefficiencies. This small message problem can be solved through aggregation strategies, however these typically require undesirable code restructuring that is cumbersome to incorporate and maintain in user applications. A strategy called “aggregation contexts” aimed at alleviating this burden has previously been proposed for the OpenSHMEM PGAS API. Despite its potential, it has not yet been validated for scalability on large systems consisting of thousands of nodes, nor proven to be performance-portable, which are critical for its adoption. In this paper, we demonstrate the scalability and performance portability of aggregation contexts using up to 8192 nodes on ORNL’s Frontier system. Our study reveals good scaling patterns while also identifying further opportunities for performance improvements to make it even more effective.