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Power Efficient Sharing-Aware GPU Data Management
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1049/iet-cdt.2014.0092openalex-snapshot
Cluster‐based approach for improving graphics processing unit performance by inter streaming multiprocessors locality
inferredcites →https://doi.org/10.1109/hpca.2014.6835937openalex-snapshot
Improving GPGPU resource utilization through alternative thread block scheduling
inferredcites →https://doi.org/10.1109/hpca.2014.6835938openalex-snapshot
MRPB: Memory request prioritization for massively parallel processors
inferredcites →https://doi.org/10.1109/iiswc.2009.5306797openalex-snapshot
Rodinia: A benchmark suite for heterogeneous computing
inferredcites →https://doi.org/10.1109/ispass.2009.4919648openalex-snapshot
Analyzing CUDA workloads using a detailed GPU simulator
inferredcites →https://doi.org/10.1109/micro.2012.16openalex-snapshot
Cache-Conscious Wavefront Scheduling
inferredcites →https://doi.org/10.1109/micro.2014.11openalex-snapshot
Adaptive Cache Management for Energy-Efficient GPU Computing
inferredcites →https://doi.org/10.1109/pact.2013.6618806openalex-snapshot
Neither more nor less: optimizing thread-level parallelism for GPGPUs
inferredcites →https://doi.org/10.1109/sc.2010.54openalex-snapshot
The Sharing Tracker: Using Ideas from Cache Coherence Hardware to Reduce Off-Chip Memory Traffic with Non-Coherent Caches
inferredcites →https://doi.org/10.1145/2540708.2540717openalex-snapshot
A locality-aware memory hierarchy for energy-efficient GPU architectures
inferredcites →https://doi.org/10.1145/2540708.2540718openalex-snapshot
Divergence-aware warp scheduling
inferredcites →https://doi.org/10.1145/2613908.2613909openalex-snapshot
Adaptive Cache Bypass and Insertion for Many-core Accelerators
inferredcites →https://doi.org/10.5555/2523721.2523745openalex-snapshot
Neither more nor less: optimizing thread-level parallelism for GPGPUs
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-24923-4_9openalex-snapshot
Leveraging Local Data Share for Efficient Stencil Computation in the Fletcher Model on AMD MI250X
inferred← citeshttps://doi.org/10.1109/cluster.2019.8891047openalex-snapshot
SMQoS: Improving Utilization and Energy Efficiency with QoS Awareness on GPUs
inferred← citeshttps://doi.org/10.1109/dac63849.2025.11133076openalex-snapshot
VISTA: Optimizing GPU Scheduling through Versatile Locality-Aware Data Sharing
inferred← citeshttps://doi.org/10.1109/hpca51647.2021.00047openalex-snapshot
Analyzing and Leveraging Decoupled L1 Caches in GPUs
inferred← citeshttps://doi.org/10.1109/hpcc64274.2024.00018openalex-snapshot
Pseudo-Cache: Extending the Access Scope of Requests with Global Perspective in GPUs
inferred← citeshttps://doi.org/10.1109/micro50266.2020.00062openalex-snapshot
Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/pact.2019.00028openalex-snapshot
Analyzing and Leveraging Remote-Core Bandwidth for Enhanced Performance in GPUs
inferred← citeshttps://doi.org/10.1109/tc.2020.3026043openalex-snapshot
MIPSGPU: Minimizing Pipeline Stalls for GPUs With Non-Blocking Execution
inferred← citeshttps://doi.org/10.1109/tcad.2023.3337192openalex-snapshot
ATA-Cache: Contention Mitigation for GPU Shared L1 Cache With Aggregated Tag Array
inferred← citeshttps://doi.org/10.1109/tpds.2019.2944602openalex-snapshot
cCUDA: Effective Co-Scheduling of Concurrent Kernels on GPUs
inferred← citeshttps://doi.org/10.1145/3280849openalex-snapshot
Improving Thread-level Parallelism in GPUs Through Expanding Register File to Scratchpad Memory
inferred← citeshttps://doi.org/10.1145/3410463.3414623openalex-snapshot
Analyzing and Leveraging Shared L1 Caches in GPUs
inferred← citeshttps://doi.org/10.1145/3429981openalex-snapshot
Efficient Nearest-Neighbor Data Sharing in GPUs
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