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A Waterfall Model to Achieve Energy Efficient Tasks Mapping for Large Scale GPU Clusters
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/047134608x.w5716openalex-snapshot
Heterogeneous Distributed Computing
inferredcites →https://doi.org/10.1002/cpe.1631openalex-snapshot
StarPU: a unified platform for task scheduling on heterogeneous multicore architectures
inferredcites →https://doi.org/10.1006/jpdc.2000.1714openalex-snapshot
A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems
inferredcites →https://doi.org/10.1007/978-3-540-92990-1_4openalex-snapshot
Predictive Runtime Code Scheduling for Heterogeneous Architectures
inferredcites →https://doi.org/10.1016/j.jpdc.2008.04.007openalex-snapshot
Just-in-time dynamic voltage scaling: Exploiting inter-node slack to save energy in MPI programs
inferredcites →https://doi.org/10.1016/j.parco.2007.09.002openalex-snapshot
Exploring weak scalability for FEM calculations on a GPU-enhanced cluster
inferredcites →https://doi.org/10.1016/s1383-7621(99)00033-8openalex-snapshot
Techniques for mapping tasks to machines in heterogeneous computing systems
inferredcites →https://doi.org/10.1109/32.41334openalex-snapshot
Allocating modules to processors in a distributed system
inferredcites →https://doi.org/10.1109/71.993206openalex-snapshot
Performance-effective and low-complexity task scheduling for heterogeneous computing
inferredcites →https://doi.org/10.1109/clustr.2009.5289128openalex-snapshot
GPU clusters for high-performance computing
inferredcites →https://doi.org/10.1109/icpads.2006.32openalex-snapshot
Critical path and area based scheduling of parallel task graphs on heterogeneous platforms
inferredcites →https://doi.org/10.1109/ipdps.2006.1639597openalex-snapshot
Profile-based optimization of power performance by using dynamic voltage scaling on a PC cluster
inferredcites →https://doi.org/10.1109/ipdps.2010.5470427openalex-snapshot
Speculative execution on multi-GPU systems
inferredcites →https://doi.org/10.1109/ispdc.2007.1openalex-snapshot
A Comparison of Scheduling Approaches for Mixed-Parallel Applications on Heterogeneous Platforms
inferredcites →https://doi.org/10.1109/micro.2003.1253186openalex-snapshot
Runtime power monitoring in high-end processors: methodology and empirical data
inferredcites →https://doi.org/10.1109/sc.2005.3openalex-snapshot
A Power-Aware Run-Time System for High-Performance Computing
inferredcites →https://doi.org/10.1109/sc.2005.39openalex-snapshot
Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save Energy in MPI Programs
inferredcites →https://doi.org/10.1109/sc.2005.57openalex-snapshot
Performance-constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters
inferredcites →https://doi.org/10.1109/sfcs.1995.492493openalex-snapshot
A scheduling model for reduced CPU energy
inferredcites →https://doi.org/10.1145/1062261.1062295openalex-snapshot
Scheduling for heterogeneous processors in server systems
inferredcites →https://doi.org/10.1145/1555754.1555775openalex-snapshot
An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness
inferredcites →https://doi.org/10.1145/1815961.1815998openalex-snapshot
An integrated GPU power and performance model
inferredcites →https://doi.org/10.1145/234313.234411openalex-snapshot
Software support for heterogeneous computing
inferredcites →https://doi.org/10.5555/956417.956567openalex-snapshot
Runtime power monitoring in high-end processors: methodology and empirical data
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.3692openalex-snapshot
Green computing on graphics processing units
inferred← citeshttps://doi.org/10.1002/cpe.5793openalex-snapshot
Adaptive and transparent task scheduling of GPU ‐powered clusters
inferred← citeshttps://doi.org/10.1007/s10586-012-0219-6openalex-snapshot
Evaluating application performance and energy consumption on hybrid CPU+GPU architecture
inferred← citeshttps://doi.org/10.1007/s10586-018-2866-8openalex-snapshot
A real-time and reliable dynamic migration model for concurrent taskflow in a GPU cluster
inferred← citeshttps://doi.org/10.1016/j.jpdc.2013.07.012openalex-snapshot
Efficient heterogeneous execution on large multicore and accelerator platforms: Case study using a block tridiagonal solver
inferred← citeshttps://doi.org/10.1016/j.jpdc.2018.05.006openalex-snapshot
A collaborative CPU–GPU approach for principal component analysis on mobile heterogeneous platforms
inferred← citeshttps://doi.org/10.1016/j.micpro.2016.05.008openalex-snapshot
Ai BCS: A GPU cluster scheduling optimization based on SKE model
inferred← citeshttps://doi.org/10.1016/s1665-6423(14)71676-1openalex-snapshot
Efficient Workload Balancing on Heterogeneous GPUs using MixedInteger Non-Linear Programming
inferred← citeshttps://doi.org/10.1109/hpcc.2014.25openalex-snapshot
Fast and Green Computing with Graphics Processing Units for Solving Sparse Linear Systems
inferred← citeshttps://doi.org/10.1109/hpcc.2014.54openalex-snapshot
Power Consumption Analysis of Parallel Algorithms on GPUs
inferred← citeshttps://doi.org/10.1109/icsai.2012.6223074openalex-snapshot
An energy efficient task scheduling scheme for heterogeneous GPU-enhanced clusters
inferred← citeshttps://doi.org/10.1109/infocom.2017.8057205openalex-snapshot
Energy efficient real-time task scheduling on CPU-GPU hybrid clusters
inferred← citeshttps://doi.org/10.1109/tpds.2022.3181096openalex-snapshot
Energy-Aware Non-Preemptive Task Scheduling With Deadline Constraint in DVFS-Enabled Heterogeneous Clusters
inferred← citeshttps://doi.org/10.1145/2636342openalex-snapshot
A Survey of Methods for Analyzing and Improving GPU Energy Efficiency
inferred← citeshttps://doi.org/10.1145/2788396openalex-snapshot
A Survey of CPU-GPU Heterogeneous Computing Techniques
inferred← citeshttps://doi.org/10.1145/3077839.3077855openalex-snapshot
Energy Efficient Job Scheduling with DVFS for CPU-GPU Heterogeneous Systems
inferred← citeshttps://doi.org/10.1145/3406208openalex-snapshot
A Taxonomy and Survey of Power Models and Power Modeling for Cloud Servers
inferred← citeshttps://doi.org/10.1145/3458817.3476223openalex-snapshot
Characterization and prediction of deep learning workloads in large-scale GPU datacenters
inferred← citeshttps://doi.org/10.1145/3797905.3800546openalex-snapshot
CATS: Correlation-aware Task Scheduling for GPU Power Optimization in AI Data Centers
inferred← citeshttps://doi.org/10.14569/ijacsa.2018.091029openalex-snapshot
Task Scheduling Frameworks for Heterogeneous Computing Toward Exascale
inferred← citeshttps://doi.org/10.32657/10356/172372openalex-snapshot
Building efficient and practical machine learning systems
inferred← citeshttps://doi.org/10.3837/tiis.2020.05.008openalex-snapshot
Low-power Scheduling Framework for Heterogeneous Architecture under Performance Constraint
inferred← citeshttps://doi.org/10.4028/www.scientific.net/amm.479-480.805openalex-snapshot
Efficient Computational Workload Distribution on Heterogeneous GPUs
inferred← citeshttps://doi.org/10.48550/arxiv.1404.4629openalex-snapshot
A Survey of Methods For Analyzing and Improving GPU Energy Efficiency
inferred← citeshttps://doi.org/10.48550/arxiv.2104.00486openalex-snapshot
Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters
inferred← citeshttps://doi.org/10.5753/wscad.2015.14288openalex-snapshot
Utilização de aceleradores embarcados de baixo consumo na implementação de sistemas de HPC
inferred← citeshttps://doi.org/10.70675/3f7377c0z6eedz48b4zb7eezf5aa2e3d1684openalex-snapshot
Méthodes numériques pour la résolution accélérée des systèmes linéaires de grandes tailles sur architectures hybrides massivement parallèles
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