Publication | Closed Access
TOP-PIM
320
Citations
36
References
2014
Year
Unknown Venue
Energy ConsumptionData MovementEngineeringData ScienceMemory-intensive ComputationsHigh-performance ArchitectureIn-storage ComputingComputer ArchitectureMemoryComputer EngineeringParallel ProgrammingComputer ScienceParallel ComputingMemory ArchitectureSocial SciencesIn-memory ComputingMulti-channel Memory Architecture
As computation becomes increasingly limited by data movement and energy consumption, exploiting locality throughout the memory hierarchy becomes critical to continued performance scaling. Moving computation closer to memory presents an opportunity to reduce both energy and data movement overheads. We explore the use of 3D die stacking to move memory-intensive computations closer to memory. This approach to processing in memory addresses some drawbacks of prior research on in-memory computing and is commercially viable in the foreseeable future.
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