Publication | Closed Access
NAPEL
86
Citations
29
References
2019
Year
Unknown Venue
Energy ConsumptionEngineeringEdge ComputingData Movement BottleneckComputer DesignCloud ComputingHigh-performance ArchitectureComputer ArchitectureComputer EngineeringParallel ProgrammingComputer ScienceParallel ComputingNmc ArchitecturesMemory Architecture
The cost of moving data between the memory/storage units and the compute units is a major contributor to the execution time and energy consumption of modern workloads in computing systems. A promising paradigm to alleviate this data movement bottleneck is near-memory computing (NMC), which consists of placing compute units close to the memory/storage units. There is substantial research effort that proposes NMC architectures and identifies workloads that can benefit from NMC. System architects typically use simulation techniques to evaluate the performance and energy consumption of their designs. However, simulation is extremely slow, imposing long times for design space exploration. In order to enable fast early-stage design space exploration of NMC architectures, we need high-level performance and energy models.
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