A complete set of spintronic hardware building blocks for low power, small footprint, high performance neuromorphic architectures

2019 ◽  
Author(s):  
Samiran Ganguly ◽  
Kerem Y. Camsari ◽  
Yunfei Gu ◽  
Mircea R. Stan ◽  
Avik W. Ghosh
2004 ◽  
Vol 39 (7) ◽  
pp. 1131-1139 ◽  
Author(s):  
T. Gemmeke ◽  
M. Gansen ◽  
H.J. Stockmanns ◽  
T.G. Noll

2021 ◽  
Author(s):  
Elyes Balti

Operational amplifier is considered as the core of the analog building blocks. High performance opamp must exhibit high gain, wide bandwidth, low power consumption and rail-to-rail output swings. In this work, we propose to design a fully-differential opamp design to satisfy certain design requirements and specifications.


Author(s):  
Anish Varghese ◽  
Bob Edwards ◽  
Gaurav Mitra ◽  
Alistair P Rendell

Energy efficiency is the primary impediment in the path to exascale computing. Consequently, the high-performance computing community is increasingly interested in low-power high-performance embedded systems as building blocks for large-scale high-performance systems. The Adapteva Epiphany architecture integrates low-power RISC cores on a 2D mesh network and promises up to 70 GFLOPS/Watt of theoretical performance. However, with just 32 KB of memory per eCore for storing both data and code, programming the Epiphany system presents significant challenges. In this paper we evaluate the performance of a 64-core Epiphany system with a variety of basic compute and communication micro-benchmarks. Further, we implemented two well known application kernels, 5-point star-shaped heat stencil with a peak performance of 65.2 GFLOPS and matrix multiplication with 65.3 GFLOPS in single precision across 64 Epiphany cores. We discuss strategies for implementing high-performance computing application kernels on such memory constrained low-power devices and compare the Epiphany with competing low-power systems. With future Epiphany revisions expected to house thousands of cores on a single chip, understanding the merits of such an architecture is of prime importance to the exascale initiative.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sarthak Gupta ◽  
Pratik Kumar ◽  
Tathagata Paul ◽  
André van Schaik ◽  
Arindam Ghosh ◽  
...  

Abstract Neuromorphic architectures have become essential building blocks for next-generation computational systems, where intelligence is embedded directly onto low power, small area, and computationally efficient hardware devices. In such devices, realization of neural algorithms requires storage of weights in digital memories, which is a bottleneck in terms of power and area. We hereby propose a biologically inspired low power, hybrid architectural framework for wake-up systems. This architecture utilizes our novel high-performance, ultra-low power molybdenum disulphide (MoS2) based two-dimensional synaptic memtransistor as an analogue memory. Furthermore, it exploits random device mismatches to implement the population coding scheme. Power consumption per CMOS neuron block was found to be 3 nw in the 65 nm process technology, while the energy consumption per cycle was 0.3 pJ for potentiation and 20 pJ for depression cycles of the synaptic device. The proposed framework was demonstrated for classification and regression tasks, using both off-chip and simplified on-chip sign-based learning techniques.


2016 ◽  
Vol 11 (1) ◽  
pp. 57-68
Author(s):  
Shruti Kalra ◽  
A. B. Bhattacharyya

Aggressive technological scaling continues to drive ultra-large-scale-integrated chips to higher clock speed. This causes large power consumption leading to considerable thermal generation and on-chip temperature gradient. Though much of the research has been focused on low power design, thermal issues still persist and need attention for enhanced integrated circuit reliability. The present paper outlines a methodology for a first hand estimating effect of temperature on basic CMOS building blocks at ultra deep submicron technology nodes utilizing modified α-power law based MOSFET model. The generalized α-power model is further applied for calculating Zero Temperature Coefficient (ZTC) point that provides temperature-independent operation of high performance and low power digital circuits without the use of conditioning circuits. The performance of basic digital circuits such as Inverter, NAND, NOR and XOR gate has been analyzed and results are compared with BSIM4 with respect to temperature up to 32nm technology node. The error lies within an acceptable range of 5-10%.


Author(s):  
A. Ferrerón Labari ◽  
D. Suárez Gracia ◽  
V. Viñals Yúfera

In the last years, embedded systems have evolved so that they offer capabilities we could only find before in high performance systems. Portable devices already have multiprocessors on-chip (such as PowerPC 476FP or ARM Cortex A9 MP), usually multi-threaded, and a powerful multi-level cache memory hierarchy on-chip. As most of these systems are battery-powered, the power consumption becomes a critical issue. Achieving high performance and low power consumption is a high complexity challenge where some proposals have been already made. Suarez et al. proposed a new cache hierarchy on-chip, the LP-NUCA (Low Power NUCA), which is able to reduce the access latency taking advantage of NUCA (Non-Uniform Cache Architectures) properties. The key points are decoupling the functionality, and utilizing three specialized networks on-chip. This structure has been proved to be efficient for data hierarchies, achieving a good performance and reducing the energy consumption. On the other hand, instruction caches have different requirements and characteristics than data caches, contradicting the low-power embedded systems requirements, especially in SMT (simultaneous multi-threading) environments. We want to study the benefits of utilizing small tiled caches for the instruction hierarchy, so we propose a new design, ID-LP-NUCAs. Thus, we need to re-evaluate completely our previous design in terms of structure design, interconnection networks (including topologies, flow control and routing), content management (with special interest in hardware/software content allocation policies), and structure sharing. In CMP environments (chip multiprocessors) with parallel workloads, coherence plays an important role, and must be taken into consideration.


Author(s):  
Hiroyuki Hakoi ◽  
Ming Ni ◽  
Junichi Hashimoto ◽  
Takashi Sato ◽  
Shinji Shimada ◽  
...  

2020 ◽  
Vol 12 (3) ◽  
pp. 168-174
Author(s):  
Rashmi Sahu ◽  
Maitraiyee Konar ◽  
Sudip Kundu

Background: Sensing of biomedical signals is crucial for monitoring of various health conditions. These signals have a very low amplitude (in μV) and a small frequency range (<500 Hz). In the presence of various common-mode interferences, biomedical signals are difficult to detect. Instrumentation amplifiers (INAs) are usually preferred to detect these signals due to their high commonmode rejection ratio (CMRR). Gain accuracy and CMRR are two important parameters associated with any INA. This article, therefore, focuses on the improvement of the gain accuracy and CMRR of a low power INA topology. Objective: The objective of this article is to achieve high gain accuracy and CMRR of low power INA by having high gain operational amplifiers (Op-Amps), which are the building blocks of the INAs. Methods: For the implementation of the Op-Amps and the INAs, the Cadence Virtuoso tool was used. All the designs and implementation were realized in 0.18 μm CMOS technology. Results: Three different Op-Amp topologies namely single-stage differential Op-Amp, folded cascode Op-Amp, and multi-stage Op-Amp were implemented. Using these Op-Amp topologies separately, three Op-Amp-based INAs were realized and compared. The INA designed using the high gain multistage Op-Amp topology of low-frequency gain of 123.89 dB achieves a CMRR of 164.1 dB, with the INA’s gain accuracy as good as 99%, which is the best when compared to the other two INAs realized using the other two Op-Amp topologies implemented. Conclusion: Using very high gain Op-Amps as the building blocks of the INA improves the gain accuracy of the INA and enhances the CMRR of the INA. The three Op-Amp-based INA designed with the multi-stage Op-Amps shows state-of-the-art characteristics as its gain accuracy is 99% and CMRR is as high as 164.1 dB. The power consumed by this INA is 29.25 μW by operating on a power supply of ±0.9V. This makes this INA highly suitable for low power measurement applications.


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