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Analyzing and Leveraging Shared L1 Caches in GPUs., , , , and . PACT, page 161-173. ACM, (2020)μC-States: Fine-grained GPU Datapath Power Management., , , , , , , , and . PACT, page 17-30. ACM, (2016)Optimizing GPU Cache Policies for MI Workloads., , , , , , , , , and 2 other author(s). IISWC, page 243-248. IEEE, (2019)Efficient synthetic traffic models for large, complex SoCs., , , , and . HPCA, page 297-308. IEEE Computer Society, (2016)Controlled Kernel Launch for Dynamic Parallelism in GPUs., , , , , , , , and . HPCA, page 649-660. IEEE Computer Society, (2017)Holistic Management of the GPGPU Memory Hierarchy to Manage Warp-level Latency Tolerance., , , , , , and . CoRR, (2018)Quantifying Data Locality in Dynamic Parallelism in GPUs., , , , , and . POMACS, 2 (3): 39:1-39:24 (2018)Analyzing and Leveraging Remote-Core Bandwidth for Enhanced Performance in GPUs., , , and . PACT, page 258-271. IEEE, (2019)Efficient and Fair Multi-programming in GPUs via Effective Bandwidth Management., , , , and . HPCA, page 247-258. IEEE Computer Society, (2018)Scheduling Techniques for GPU Architectures with Processing-In-Memory Capabilities., , , , , , , and . PACT, page 31-44. ACM, (2016)