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ID-cache: instruction and memory divergence based cache management for GPUs.

, , and . IISWC, page 158-167. IEEE Computer Society, (2016)

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Understanding the thermal challenges of high-performance mobile devices with a detailed platform temperature model., and . IISWC, page 122-123. IEEE Computer Society, (2017)Exploiting Parallelism Opportunities with Deep Learning Frameworks., , , , and . CoRR, (2019)Emerging Neural Workloads and Their Impact on Hardware., , , , , , , , , and 5 other author(s). DATE, page 1462-1471. IEEE, (2020)DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference., , , , , , , , and . ISCA, page 982-995. IEEE, (2020)MCM-GPU: Multi-Chip-Module GPUs for Continued Performance Scalability., , , , , , , , and . ISCA, page 320-332. ACM, (2017)Configurable-ECC: Architecting a Flexible ECC Scheme to Support Different Sized Accesses in High Bandwidth Memory Systems., , , , and . IEEE Trans. Computers, 68 (5): 646-659 (2019)Genetic improvement of GPU code., , and . GI@ICSE, page 20-27. ACM, (2019)LATTE-CC: Latency Tolerance Aware Adaptive Cache Compression Management for Energy Efficient GPUs., , , and . HPCA, page 221-234. IEEE Computer Society, (2018)Improving smartphone user experience by balancing performance and energy with probabilistic QoS guarantee., , and . HPCA, page 52-63. IEEE Computer Society, (2016)CAWA: coordinated warp scheduling and cache prioritization for critical warp acceleration of GPGPU workloads., , and . ISCA, page 515-527. ACM, (2015)