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Efficient Dynamic Device Placement for Deep Neural Network Training on Heterogeneous Systems.

, , and . SAMOS, volume 11733 of Lecture Notes in Computer Science, page 51-64. Springer, (2019)

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Exploiting SIMD capability in an ARMv7-to-ARMv8 dynamic binary translator., , , , , and . CASES, page 14:1-14:3. ACM, (2018)Dynamic tuning of applications using restricted transactional memory., , , , and . RACS, page 249-254. ACM, (2018)Exploiting Longer SIMD Lanes in Dynamic Binary Translation., , , , and . ICPADS, page 853-860. IEEE Computer Society, (2016)Efficient Dynamic Device Placement for Deep Neural Network Training on Heterogeneous Systems., , and . SAMOS, volume 11733 of Lecture Notes in Computer Science, page 51-64. Springer, (2019)Exploiting Vector Processing in Dynamic Binary Translation., , , , , and . ICPP, page 93:1-93:10. ACM, (2019)Automatically Migrating Sequential Applications to Heterogeneous System Architecture., , , and . HPCS, page 114-121. IEEE, (2018)Exploiting SIMD Asymmetry in ARM-to-x86 Dynamic Binary Translation., , , , and . ACM Trans. Archit. Code Optim., 16 (1): 2:1-2:24 (2019)Processor-Tracing Guided Region Formation in Dynamic Binary Translation., , , , and . ACM Trans. Archit. Code Optim., 15 (4): 52:1-52:25 (2019)Dynamic translation of structured Loads/Stores and register mapping for architectures with SIMD extensions., , , , and . LCTES, page 31-40. ACM, (2017)Translating Traditional SIMD Instructions to Vector Length Agnostic Architectures., and . CGO, page 275. IEEE, (2019)