Networked Power-Gated MRAMs for Memory-Based Computing
Emerging nonvolatile memory technologies open new perspectives for original computing architectures. In this paper, we propose a new type of flexible and energy-efficient architecture that relies on power-gated distributed magnetoresistive random access memory (MRAM). The proposed architecture uses...
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| Vydáno v: | IEEE transactions on very large scale integration (VLSI) systems Ročník 26; číslo 12; s. 2696 - 2708 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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IEEE
01.12.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1063-8210, 1557-9999 |
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| Abstract | Emerging nonvolatile memory technologies open new perspectives for original computing architectures. In this paper, we propose a new type of flexible and energy-efficient architecture that relies on power-gated distributed magnetoresistive random access memory (MRAM). The proposed architecture uses a network-on-chip (NoC) to interconnect MRAM-based clusters, processing elements, and managers. The NoC distributes application-specific commands to MRAM devices by means of packets. Configurable network interfaces allow to transform MRAM devices into smart units able to respond to incoming commands. In this context, three types of MRAM designs are proposed with different power-gating policies and granularities. A relevant database search engine case study is considered to illustrate the benefits of this proposed architecture. It is implemented with a sparse-neural-network approach and simulated in SystemC with different scenarios including hundreds of database queries. Hardware designs and accurate power estimations have been conducted. The obtained results demonstrate important power reduction with database hit rates of about 94%. Targeting 65-nm technology, energy savings reach 87% when compared with an static random access memory-based implementation. Moreover, a new asymmetric read/write MRAM type provides from 39% to 50% energy reduction with respect to the other fixed-granularity models. This results in a low-power, highly scalable, and configurable implementation of memory-based computing. |
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| AbstractList | Emerging non-volatile memory technologies open new perspectives for original computing architectures. In this paper, we propose a new type of flexible and energy-efficient ar- chitecture that relies on power-gated distributed Magnetoresistive Random-Access Memory (MRAM). The proposed architecture uses a Network-on-Chip (NoC) to interconnect MRAM-based clusters, processing elements, and managers. The NoC distributes application-specific commands to MRAM devices by means of packets. Configurable Network Interfaces (NI) allow to transform MRAM devices into smart units able to respond to incoming commands. In this context, three types of MRAM designs are proposed with different power-gating policies and granularities. A relevant database search engine case study is considered to illus- trate the benefits of this proposed architecture. It is implemented with a Sparse-Neural-Network (SNN) approach and simulated in SystemC with different scenarios including hundreds of database queries. Hardware designs and accurate power estimations have been conducted. The obtained results demonstrate important power reduction with database hit rates of about 94%. Targeting 65nm technology, energy savings reach 87% when compared with an SRAM-based implementation. Moreover, a new asymmetric read/write MRAM type provides from 39% to 50% energy reduction with respect to the other fixed-granularity models. This results in a low-power, highly scalable and configurable implementation of memory-based computing. Emerging nonvolatile memory technologies open new perspectives for original computing architectures. In this paper, we propose a new type of flexible and energy-efficient architecture that relies on power-gated distributed magnetoresistive random access memory (MRAM). The proposed architecture uses a network-on-chip (NoC) to interconnect MRAM-based clusters, processing elements, and managers. The NoC distributes application-specific commands to MRAM devices by means of packets. Configurable network interfaces allow to transform MRAM devices into smart units able to respond to incoming commands. In this context, three types of MRAM designs are proposed with different power-gating policies and granularities. A relevant database search engine case study is considered to illustrate the benefits of this proposed architecture. It is implemented with a sparse-neural-network approach and simulated in SystemC with different scenarios including hundreds of database queries. Hardware designs and accurate power estimations have been conducted. The obtained results demonstrate important power reduction with database hit rates of about 94%. Targeting 65-nm technology, energy savings reach 87% when compared with an static random access memory-based implementation. Moreover, a new asymmetric read/write MRAM type provides from 39% to 50% energy reduction with respect to the other fixed-granularity models. This results in a low-power, highly scalable, and configurable implementation of memory-based computing. |
| Author | Baghdadi, Amer Sepulveda, Johanna Diguet, Jean-Philippe Rizk, Mostafa Hanyu, Takahiro Onizawa, Naoya |
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| SubjectTerms | Bandwidth Computation Computer architecture Computer Arithmetic Computer memory Computer Science Computer simulation Distributed memory Distributed, Parallel, and Cluster Computing Electric power distribution Electronics Embedded Systems Energy management Engineering Sciences Information Theory magnetoresistive random access memory (MRAM) Magnetoresistivity Micro and nanotechnologies Microelectronics Microprocessors network-on-chip (NoC) Networking and Internet Architecture Neural networks Nonvolatile memory power gating (PG) Power management Random access memory Reduction Search engines Signal and Image Processing sparse neural networks (SNNs) Static random access memory System on chip |
| Title | Networked Power-Gated MRAMs for Memory-Based Computing |
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