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Over the past few years, the explosion in sparse tensor algebra workloads hasled to a corresponding rise in domain-specific accelerators to service them.Due to the irregularity present in sparse tensors, these accelerators employ awide variety of novel solutions to achieve good performance. At the same time,prior work on design-flexible sparse accelerator modeling does not express thisfull range of design features, making it difficult to understand the impact ofeach design choice and compare or extend the state-of-the-art.  To address this, we propose TeAAL: a language and simulator generator for theconcise and precise specification and evaluation of sparse tensor algebraaccelerators. We use TeAAL to represent and evaluate four disparatestate-of-the-art accelerators -- ExTensor, Gamma, OuterSPACE, and SIGMA -- andverify that it reproduces their performance with high accuracy. Finally, wedemonstrate the potential of TeAAL as a tool for designing new accelerators byshowing how it can be used to speed up vertex-centric programming accelerators-- achieving $1.9\times$ on BFS and $1.2\times$ on SSSP over GraphDynS.

TeAAL: A Declarative Framework for Modeling Sparse Tensor Accelerators