Efficient Power Consumption using Hybrid Emerging Memory Technology for 3D CMPs

Autor: Furat Al-Obaidy, Arghavan Asad, Farah Mohammadi
Rok vydání: 2020
Předmět:
Zdroj: LASCAS
DOI: 10.1109/lascas45839.2020.9069014
Popis: The development of computing systems, data analytics, and storages for big data computing has resulted in an increasing need for low-power computational platforms and high-performance efficiency, capable of adjusting the processing capability and storage domains. In this context, high performance acts as a critical issue in future CMPs with restricted of battery lifetime and power consumption. For future CMPs architecting, 3D stacking of Last Level Cache (LLC) has been recently introduced as a new methodology to combat the performance challenges of 2D integration. We propose an uncore hybrid LLC which takes advantage of emerging memory technologies. In the former phase, a reconfiguration unit premised on a simple convex formulation is used to forecast the running application’s bandwidth and selects a high-performance configuration aimed at the LLC. The experimental results showed a reduction in (average memory access time) AMAT 12% as compared to SRAM- cache for PARSEC benchmarks which lead to 88% minimization in power consumption on average.
Databáze: OpenAIRE