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RAID+: Deterministic and Balanced Data Distribution for Large Disk Enclosures.

, , , , , and . FAST, page 279-294. USENIX Association, (2018)

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Performance Analysis of GPU-Based Convolutional Neural Networks., , , , and . ICPP, page 67-76. IEEE Computer Society, (2016)Dayu: Fast and Low-interference Data Recovery in Very-large Storage Systems., , , , and . USENIX Annual Technical Conference, page 993-1008. USENIX Association, (2019)HyConv: Accelerating Multi-Phase CNN Computation by Fine-Grained Policy Selection., , , and . IEEE Trans. Parallel Distributed Syst., 30 (2): 388-399 (2019)Adaptive Multiple Appearances Model Framework for Long-Term Robust Tracking., , , , and . PCM (1), volume 9314 of Lecture Notes in Computer Science, page 160-170. Springer, (2015)Determining Data Distribution for Large Disk Enclosures with 3-D Data Templates., , , , , and . ACM Trans. Storage, 15 (4): 27:1-27:38 (2020)RAID+: Deterministic and Balanced Data Distribution for Large Disk Enclosures., , , , , and . FAST, page 279-294. USENIX Association, (2018)