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Communication Dans Un Congrès Année : 2021

Instruction Set Design Methodology for In-Memory Computing through QEMU-based System Emulator

Résumé

In-Memory Computing (IMC) is a promising paradigm to mitigate the von Neumann bottleneck. However its evaluation on complete applications in the context of full-scale systems is limited by the complexity of simulation frameworks as well is the disjunction between hardware exploration and compiler support. This paper proposes a global exploration flow in the scale of Instruction Set Architectures (ISA) to perform both modeling and the generation of compiler support to perform ISA-level exploration. Our emulation methodology is based on QEMU, implements a performance model based on hardware characterizations from the State-of-the-Art, and allows the modeling of cache hierarchies, while our compiler support is automatically generated and based on a specialized compiler. We evaluate three applications in the domains of image processing and linear algebra on a reference IMC architecture, and analyze the obtained results to validate our methodology.
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Dates et versions

hal-03449840 , version 1 (02-12-2021)

Identifiants

  • HAL Id : hal-03449840 , version 1

Citer

Kévin Mambu, Henri-Pierre Charles, Julie Dumas, Maha Kooli. Instruction Set Design Methodology for In-Memory Computing through QEMU-based System Emulator. 32rd International Workshop on Rapid System Prototyping, Oct 2021, Rennes (Virtual Conference), France. ⟨hal-03449840⟩
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