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With the waning of Moore’s Law and the end of Dennard’s Scaling, systems are turning towards heterogeneity, mixing conventional cores and specialized accelerators to continue scaling performance and energy efficiency. Specialized accelerators are frequently used to improve the efficiency of computations that run inefficiently on conventional, general-purpose processors. As a result, systems ranging from smartphones to data-centers, hyper-scalars, and supercomputers are increasingly using large numbers of accelerators to provide better efficiency than CPU-based solutions. However, heterogeneous systems face key challenges: changes to the underlying technology which threaten continued scaling, as well as the voracious scaling from applications, which require additional research to address. Traditionally, simulators could be used to perform early exploration for this research. However, existing simulators lack important support for these key challenges. Detailed simulation of modern systems can take extremely long times in existing tools and infrastructure. Furthermore, prototyping optimizations at scale can also be challenging, especially for newly proposed accelerators. Although other simulators such as Accel-Sim, SCALE-Sim, and Gemmini enable some early experiments, they are limited in their ability to target a wide variety of accelerators. In comparison, gem5 has support for various CPUs, GPUs, DSPs, and many other important accelerators. However, efficiently simulating large-scale workloads on gem5’s cycle-level models requires prohibitively long times. We aim to enhance gem5’s support to make running these workloads practical while retaining accuracy.