ReLOPE: Resistive RAM-Based Linear First-Order Partial Differential Equation Solver
| Autor: | Sina Sayyah Ensan, Swaroop Ghosh |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Very-large-scale integration
Partial differential equation Artificial neural network Computer science Numerical analysis First-order partial differential equation 02 engineering and technology Solver 020202 computer hardware & architecture Computational science Resistive random-access memory Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Boundary value problem Electrical and Electronic Engineering Software |
| Zdroj: | IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 29:237-241 |
| ISSN: | 1557-9999 1063-8210 |
| DOI: | 10.1109/tvlsi.2020.3035769 |
| Popis: | Data movement between memory and processing units poses an energy barrier to Von-Neumann-based architectures. In-memory computing (IMC) eliminates this barrier. RRAM-based IMC has been explored for data-intensive applications, such as artificial neural networks and matrix-vector multiplications that are considered as “soft” tasks where performance is a more important factor than accuracy. In “hard” tasks such as partial differential equations (PDEs), accuracy is a determining factor. In this brief, we propose ReLOPE, a fully RRAM crossbar-based IMC to solve PDEs using the Runge–Kutta numerical method with 97% accuracy. ReLOPE expands the operating range of solution by exploiting shifters to shift input data and output data. ReLOPE range of operation and accuracy can be expanded by using fine-grained step sizes by programming other RRAMs on the BL. Compared to software-based PDE solvers, ReLOPE gains $31.4\times $ energy reduction at only 3% accuracy loss. |
| Databáze: | OpenAIRE |
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