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A$^{2}$utoLPBench offers an endless stream of dynamically generated LP problems, ensuring agents can be tested against fresh challenges without the risk of training data leakage.
Securing DNN accelerators doesn't have to break the bank: this co-design framework slashes memory overhead by 87% while boosting performance by 12%.
