Miquel Moretó Planas

Roberto Giorgi, Miquel Moretó Planas

FREESS (Free Educational Superscalar Simulator) is an open-source teaching environment for instruction-level parallelism in a RISC-V-inspired superscalar processor. It provides a compact, cycle-by-cycle view of register renaming, issue, execution, write-back, commit, and memory ordering in a Tomasulo-style machine. The simulator exposes the register map, free pool, instruction window, reorder buffer, and load/store queues in one textual representation, so the evolution of the hardware state can be followed on screen and reproduced on paper. Runtime parameters such as issue width, queue sizes, and functional-unit latencies can be changed easily, enabling direct comparison among alternative superscalar organizations. The tool has supported Advanced Computer Architecture teaching for about fifteen years and is publicly available on GitHub.

Marco Siracusa, Olivia Hsu, Victor Soria-Pardos et al.

Irregular embedding lookups are a critical bottleneck in recommender models, sparse large language models, and graph learning models. In this paper, we first demonstrate that, by offloading these lookups to specialized access units, Decoupled Access-Execute (DAE) processors achieve 2.6$\times$ higher performance and 6.4$\times$ higher performance/watt than GPUs on end-to-end models. Then, we propose the Ember compiler for automatically generating optimized DAE code from PyTorch and TensorFlow. Conversely from other DAE compilers, Ember features multiple intermediate representations specifically designed for different optimization levels. In this way, Ember can implement all optimizations to match the performance of hand-written code, unlocking the full potential of DAE architectures at scale.