An asynchronous power aware and adaptive NoC based circuit

In todaypsilas technology generations, e.g. 90 and 65 nm, the static power consumption becomes a major contributor to the total power consumption. It is therefore important to consider all abstraction levels to reduce this power. This paper focuses on the arithmetic level and shows a methodology for a substantial reduction of the static power consumption. Both the dynamic and static power consumption is evaluated for bit-parallel and bit-serial arithmetic. Simulations are done in a typical 130 nm technology. With only a minor cost in dynamic power consumption, a static power reduction up to 13 times is shown by using bit-serial arithmetic.

Reducing the power consumption is one of the most important design problems at present. Modern microprocessors employ caches to bridge the great speed variance between the main memory and the central processing unit, but these caches propose larger and larger proportion in the total power consumption. In fact, many values rarely need the full-bit dynamic range supported by a cache. The Narrow-Width Value (NWV) occupies a large portion of cache access and storage. It is unreasonable that the storage space for value of any data width is the same in the cache, even if NWV needs only a few bits to be stored. This paper proposes a Variable Bitline Data Cache (VBDC) which exploits the popularity of NWV stored in the cache. In VBDC design, the cache data array is divided into several sub-arrays to adapt each data pattern with the different bitline length to access. The VBDC can shut off the corresponding unused high arrays to reduce its dynamic and static power consumption. The VBDC achieves low power consumption through reducing the bitline length. Experimental results employing SPEC 2000 benchmarks show that our proposed VBDC can reduce both the dynamic power consumption ant the static power consumption by 44.75% and 42.86%.

Static power due to leakage current will become a major source of power consumption in the nanometer technology era. In this paper, we propose a simple yet effective technique to reduce both static and dynamic power consumption in the scan test process. The leakage current is restrained by selecting a good primary input vector to control the paths of leakage current during the scan shift process, and this vector can also be used to reduce dynamic power. However, the reverse is not always true. A heuristic algorithm is presented to find such vectors. The proposed method is simulated by SPICE with BPTM 22nm transistor model, and the results show that on the average 15% total power reduction is achievable by the proposed method.

Personal portable devices such as DMB (digital multimedia broadcasting)s, PMP (portable multimedia player)s and PDA (portable digital assistant)s require long battery life without reducing their performance. Power consumption is one of important factors in ubiquitous environments. To reduce the dynamic power consumption, many researches have been conducted on the dynamic voltage and frequency scaling (DVFS). DVFS can reduce the power consumption proportionally to the square of the supply voltage. But processor operation under the critical speed increases the leakage current. Larger leakage current increases the static power consumption. This paper proposes a new power-aware scheduling algorithm that reduces the static and dynamic power consumption to use frequency scaling between two discrete voltage levels and under the critical speed while meeting the deadline of given applications. The simulation and experimental implementation show that the proposed scheduling algorithm results in up to 25% energy gains over traditional DVFS algorithms with two task scheduling policies.

A low power voltage management technique is proposed to reduce power consumption for domino circuits. Exploiting a rising and charge-sharing voltage allow the domino circuits to have both high performance and low power consumption. A test chip has been successfully validated to achieve 68% dynamic power consumption and 15% static power consumption respectively using TSMC 0.13um CMOS technology.

Power consumption during test mode is much higher than in normal mode of operation. This paper addresses issue of assigning suitable values to the unspecified bits (don't care) in the test patterns so that both static and dynamic power consumption during testing is reduced. We have used a genetic algorithm based heuristic to fill the don't cares. Our approach produces an average percentage improvement of 31.9, 37.0, and 37.7 in dynamic power and 3.0, 7.4, and 5.3 leakage power over 0-fill, 1-fill, and MT-fill algorithms for don't care filling, considering the test patterns having unspecified bits in ISCAS'89 benchmark suite.

A new scheme to reduce the power consumption of static random access memories is presented. It is shown that using segmented virtual grounding (SVGND), it is possible to reduce both dynamic and static power consumption. The leakage power of the cells is reduced by reducing the voltage drop over a cell. The dynamic power dissipation is also reduced by eliminating the power consumption due to the discharge of the nondesired neighboring bitlines. The effectiveness of this scheme is compared to recently reported low-power schemes. It is shown that unlike those schemes, SVGND can accommodate multiple words in one row; a significant improvement in soft error rate tolerance

Network-on-Chip (NoC) is a key element in the total power consumption of a chip multiprocessor. Dynamic Voltage Scaling is a promising method for power saving in NoCs since it contributes to reduction in both static and dynamic power consumptions. In this paper, we propose a novel scheme to reduce on-chip network power consumption when the number of Virtual Channels (VCs) with active allocation requests per cycle is less than the number of total VCs. In our method, we introduce a reconfigurable arbitration logic which can be configured to have multiple latencies and hence, multiple slack times. The increased slack times are then used to reduce the supply voltage of the routers in order to reduce the power consumption. By using this method, we manage to save power by up to 45.7% compared to a baseline architecture without any performance loss.

Current superscalar processors access the BTB early to anticipate the branch/jump target address. This access is frequent and aggressively performed since the BTB is accessed every cycle for all instructions in the ICache line being fetched. This fact increases the power density, which could create hot spots, thus increasing packaging and cooling costs. Power consumption in the BTB comes mostly from its two main fields: the tag and the target address fields. Reducing the length of either of these fields reduces power consumption, silicon area and access time. This paper analyzes at what extent tag and target address lengths could be reduced to benefit both dynamic and static power consumption, silicon area, and access time, while sustaining performance. Experimental results show that the tag length and the target address could be reduced by about a half and one byte, respectively with no performance losses. BTB peak power savings can reach about 35% when both reductions are combined together, thus effectively attacking the hot-spot.

This paper presents a QRS detector operating in multi-mode with low complexity, power saving consumption for implantable pacemaker IC. The complexity of detector is optimized after testing dynamic range of internal signals. Correspondingly, static power consumption is reduced significantly. The dynamic power consumption is saved by using down-sampling rate structure and turning off de- active filter banks bases on noise estimation. This QRS detector is evaluated with MIT-BIH Arrhythmia database archives >99% detection ratio. A soft IP core is prototyped on FPGA and synthesized by Samsung 0.18um standard library.

Due to scaling, many limitation arise for CMOS-based design memory cells in the nanometre regime, i.e. it becomes necessary to find a substitute for this design. Low power and high speed integrated circuits (ICs) are the demand of the electronics industry in many applications such as Internet of things (IoT) and electronics gadgets, e.g. Mobile, Laptops etc. Now, modern design ICs uses carbon nanotube FET or FinFET to design memory cells because of their excellent features of having low leakage and delay and improved performance. In this paper, two 10 transistor (10 T) FinFET design SRAM cells are proposed along with their hold, read, and write static noise margins (HSNM, RSNM, and WSNM), dynamic and static power consumption. These cells consume low power and provide high stability for electronic gadgets. In the proposed cells, we used a separate read and write path and back gate control method (BG). A comparative analysis of the proposed cells is done with the existing 10 T CMOS and FinFET based cells. All cells are simulated by using the tool HSPICE at 32 nm technology for a supply of 0.5 V. Cells 1 and 2 dissipate 69% and 85% less static power, 54% and 68% less read power and 17% and 56% less write power, respectively, compared to the 10 T FinFET cell. Results signify that the proposed independent gate (IG) FinFET based cells have the highest value of margins and the least value power consumption.

-As the demand for low-power, high-performance memory systems grows, the design of efficient SRAM (Static Random Access Memory) cells becomes increasingly crucial. This paper explores the power consumption, performance, and stability of two SRAM cell designs: the conventional 6T and the Single Ended 6T SRAM. While the conventional 6T SRAM is prone to read disturb noise and high leakage power, it remains widely used due to its simplicity and compactness. To address these issues, the Single Ended 6T SRAM cell is introduced as an alternative, which reduces both power consumption and area while maintaining competitive performance. The study provides a detailed analysis of static and dynamic power consumption, read/write stability, and overall energy efficiency for both cell architectures. Simulation results show that the Single Ended 6T SRAM offers significant improvements in power reduction without compromising speed, making it a promising solution for future low-power, high-performance memory applications. Keywords— SRAM cell, Pre-Charge Circuits, Sense Amplifiers, and Single-Ended vs. Conventional 6T SRAM Cell.

One of the biggest problems in complicated and high-performance SoC design is management of energy and/or power consumption. In this chapter, we present energy management techniques in system design including HW and SW, SoC architecture and logic design. Dynamic power consumption is the major factor of energy consumption in the current CMOS digital circuits. The dynamic power consumption is affected by supply voltage, load capacitance and switching activity. We present approaches to controlling supply voltage, load capacitance and switching activity dynamically and statically in system architecture and algorithm design levels. We also discuss about the memory architecture for reducing power and energy in HW and SW co-design of SoC. In the future CMOS technology, leakage power consumption becomes dominant, because the threshold voltages are scaled as the transistor size shrinks. We summarize the techniques for reducing leakage power in system architecture design. The contents of the chapter include the following issues; (1) power and energy consumptions in SoC design, (2) tradeoff between energy and performance, (3) tradeoff among energy, QoS (i.e., latency and computational precision), reliability, and flexibility (4) techniques for reducing dynamic power consumption, and (5) leakage power reduction techniques

The rapid evolution of semiconductor integrated circuits toward nanoscale process technologies has fundamentally transformed the design paradigm, elevating power consumption from a secondary consideration to a primary design constraint. Power-aware physical design methodologies have emerged as essential frameworks that systematically integrate power optimization objectives throughout the entire implementation process, addressing the complex challenges posed by escalating dynamic and static power consumption in advanced technology nodes. This article encompasses comprehensive strategies including multi-voltage domain architectures, sophisticated clock management techniques, power-aware placement and routing algorithms, and advanced verification frameworks that ensure power intent preservation. Contemporary developments incorporate machine learning techniques, statistical optimization approaches, and three-dimensional integration technologies that extend power optimization capabilities beyond traditional chip-level boundaries. The integration of power considerations across logical and physical design domains enables coordinated optimization strategies that balance power efficiency with performance requirements while maintaining design robustness across process variations and operating conditions. Advanced packaging techniques and system-level power management strategies provide additional optimization opportunities through heterogeneous integration and cross-layer coordination mechanisms. The article demonstrates that power-aware design methodologies are fundamental enablers for energy-efficient computing systems, supporting the evolving requirements of mobile electronics, data processing systems, and embedded platforms while addressing the sustainability concerns of contemporary semiconductor applications.

With the rapid evolution of network speed from 1Gbps to 10Gbps, a wide spectrum of research has been done on TCP/IP to improve its processing efficiency on general purpose processors. However, most of them did studies only from the performance perspective and ignored its power efficiency. As power has become a major concern in data centers, where servers are often interconnected with 10GbE, it becomes critical to understand power efficiency of TCP/IP packet processing over 10GbE. In this paper, we extensively examine power consumption of TCP/IP packet processing over 10GbE on Intel Nehalem platforms across a range of I/O sizes by using a power analyzer. In order to understand the power consumption, we use an external Data Acquisition System (DAQ) to obtain a breakdown of power consumption for individual hardware components such as CPU, memory and NIC etc. In addition, as integrated NIC architectures are gaining more attention in high-end servers, we also study power consumption of TCP/IP packet processing on an integrated NIC by using a Sun Niagara 2 processor with two integrated 10GbE NICs. We carefully compare the power efficiency of using an integrated NIC with using a PCI-E based discrete NIC. We make many new observations as follows: 1) Unlike 1GbE NICs, 10GbE NICs have high idle power dissipation, and TCP/IP packet processing over 10GbE consumes significant dynamic power. 2) Our power breakdown reveals that CPU is the major source of the dynamic power consumption, followed by memory. As the I/O size increases, the CPU power consumption reduces but the memory power consumption grows. Compared to CPU and memory, NIC has low dynamic power consumption. 3) Large I/O sizes are much more power efficient than small I/O sizes. 4) While integrating a 10GbE NIC slightly increases CPU power consumption, it not only reduces system idle power dissipation due to elimination of PCI-E interface in NICs, but also achieves dynamic power savings due to better processing efficiency. Our studies motivate us to design a more power efficient server architecture, which can be used in the next generation data centers.