A Sub-µW Reversed-Body-Bias 8-bit Processor on 65-nm Silicon-On-Thin-Box (SOTB) for IoT Applications

Abstract : For most Internet-of-Things (IoT) applications, embedded processors typically execute lightweight tasks such as sensing and communication. The typical IoT program senses some information and sends them via a channel, usually a wireless channel with an RF circuit. These IoT nodes often require a system with networking capabilities and a low-power harvester implementation. This paper presents a sub-µW 8-bit processor which is suitable for such IoT applications. The processor implements the Open8 Instruction Set Architecture (ISA) with an 8-bit datapath and 16-bit bus addressing. The chip contains the processor and a 4-KB of Static Random-Access-Memory (SRAM), and is fabricated by the 65-nm Silicon-On-Thin-Box (SOTB) process. The SOTB process is one of the Fully-Depleted Silicon-On-Insulator (FD-SOI) technology. Hence, the ability to control biasing voltages is one of its key advantages to achieve low-power. The experimental results show that the power consumption at the reverse-body bias can reach down to 50-nW with 0.5-V supply voltage and 32-KHz operating clock frequency. The completed microcontroller consists of the Open8 processor, 32-KB of Read-Only-Memory (ROM), 4-KB of SRAM, Serial Peripheral Interface (SPI), SPI programmer, debug module, General-Purpose In-Outs (GPIOs), and UART. The system was tested using an XC7A100T Xilinx Field-Programmable Gate Array (FPGA); it yielded 1.8% of the total FPGA utilization.

 EXISTING SYSTEM :

 ? The biasing control of asynchronous sub-systems in FD-SOI 28 nm requires designing and analyzing dedicated cells that do not exist in the standard cell libraries. ? WCLS is quite similar to CMLS in, however a fundamental difference exists at gate terminals of transistors 3 and 4 that are connected, respectively, to the signals FB and FB of the output buffers. ? Granularity means how many Body Biasing Domains exists in a given circuit. The first presented approach illustrates whats is called a coarse-grain strategy. ? If the same region aforementioned is divided into more Body Biasing Domains, finer is the strategy. The control is equally divided, in order to bias only the activated stages.

 DISADVANTAGE :

 ? To overcome these problems, we have now devised a model that includes BB switching overhead, and it is suitable for optimization methodologies. ? The problem is the optimization of energy consumption by finding the optimal VBN and VDD voltages, constrained by the switching overhead penalties and energy waste. ? This is thus a problem of finding the minimum constrained nonlinear multi-variable equation. ? The IPM has been proven to achieve an optimal solution efficiently for these types of optimization problems. ? Its convergence advantage and computational efficiency make IPM an excellent problem-solving method for NLP.

 PROPOSED SYSTEM :

 • We proposed a distributed activity-driven strategy easily managing a large number of Body-Biasing Domains (BBDs). • Several electric-level simulations were done to determine the lowest operation voltages of the proposed C-element schemes. • The activity detection proposed in this case is a simplified version of the emptiness detector of the system-level approach. • The proposed return signals play to isolate the pull-up networks from the pull-down networks of the LS, further weakening the competition between the currents coming from pull-up transistors and the currents going to pull-down transistors. • Some proposed techniques using charge-pumps and digital-to-analog converters are interesting for large IPs, but they require an important area.

 ADVANTAGE :

 ? Body bias (BB) control is attracting the attention of designers as a means of controlling the tradeoff between leakage power and performance without affecting power supply . ? It is especially efficient in fully depleted silicon-on-insulator (FD-SOI) technology , which is commonly used for low-power systems. ? It features latch-up immunity, high temperature tolerance, high performance, radiation hardness, and high BB sensitivity due to its insulating buried oxide layer, which is widely used in SOI devices. ? The energy of real-time systems for embedded usage needs to be efficient without affecting the system’s ability to meet task deadlines. ? Although these techniques improve energy efficiency, they often require a significant amount of power, since they must directly control the system supply voltage.