RingScalar: A Complexity-Effective Out-of-Order Superscalar Microarchitecture

RingScalar is a complexity-effective microarchitecture for out-of-order superscalar processors, that reduces the area, latency, and power of all major structures in the instruction flow. The design divides an N-way superscalar into N columns connected in a unidirectional ring, where each column contains a portion of the instruction window, a bank of the register file, and an ALU. The design exploits the fact that most decoded instructions are waiting on just one operand to use only a single tag per issue window entry, and to restrict instruction wakeup and value bypass to only communicate with the neighboring column. Detailed simulations of four-issue single-threaded machines running SPECint2000 show that RingScalar has IPC only 13% lower than an idealized superscalar, while providing large reductions in area, power, and circuit latency

Direct instruction wakeup for out-of-order processors

Instruction queues consume a significant amount of power in high-performance processors, primarily due to instruction wakeup logic access to the queue structures. The wakeup logic delay is also a critical timing parameter. This paper proposes a new queue organization using a small number of successor pointers plus a small number of dynamically allocated full successor bit vectors for cases with a larger number of successors. The details of the new organization are described and it is shown to achieve the performance of CAM-based or full dependency matrix organizations using just one pointer per instruction plus eight full bit vectors. Only two full bit vectors are needed when two successor pointers are stored per instruction. Finally, a design and pre-layout of all critical structures in 70 nm technology was performed for the proposed organization as well as for a CAM-based baseline. The new design is shown to use 1/2 to 1/5th of the baseline instruction queue power, depending on queue size. It is also shown to use significantly less power than the full dependency matrix based design.Peer ReviewedPostprint (published version

A Review of Energy Conservation in Wireless Sensor Networks

In wireless sensor networks, energy efficiency plays a major role to determine the lifetime of the network. The network is usually powered by a battery which is hard to recharge. Hence, one major challenge in wireless sensor networks is the issue of how to extend the lifetime of sensors to improve the efficiency. In order to reduce the rate at which the network consumes energy, researchers have come up with energy conservation techniques, schemes and protocols to solve the problem. This paper presents a brief overview of wireless sensor networks, outlines some causes of its energy loss and some energy conservation schemes based on existing techniques used in solving the problem of power management. Keywords: Wireless sensor network, Energy conservation, Duty cycling and Energy efficiency

A low-power cache system for high-performance processors

制度:新 ; 報告番号:甲3439号 ; 学位の種類:博士(工学) ; 授与年月日:12-Sep-11 ; 早大学位記番号:新576

Optimizing Embedded Software of Self-Powered IoT Edge Devices for Transient Computing

IoT edge computing becomes increasingly popular as it can mitigate the burden of cloud servers significantly by offloading tasks from the cloud to the edge which contains the majority of IoT devices. Currently, there are trillions of edge devices all over the world, and this number keeps increasing. A vast amount of edge devices work under power-constrained scenarios such as for outdoor environmental monitoring. Considering the cost and sustainability, in the long run, self-powering through energy harvesting technology is preferred for these IoT edge devices. Nevertheless, a common and critical drawback of self-powered IoT edge devices is that their runtime states in volatile memory such as SRAM will be lost during the power outage. Thanks to the state-of-the-art non-volatile processor (NVP), the runtime volatile states can be saved into the on-chip non-volatile memory before the power outage and recovered when harvesting power becomes available. Yet the potential of a self-powered IoT edge device is still hindered by the intrinsic low energy efficiency and reliability. In order to fully exert the potentials of existing self-powered IoT edge devices, this dissertation aims at optimizing the energy efficiency and reliability of self-powered IoT edge devices through several software approaches. First, to prevent execution progress loss during the power outage, NVP-aware task schedulers are proposed to maximize the overall task execution progress especially for the atomic tasks of which the unfinished progress is subjected to loss regardless of having been checkpointed. Second, to minimize both the time and energy overheads of checkpointing operations on non-volatile memory, an intelligent checkpointing scheme is proposed which can not only ensure a successful checkpointing but also predict the necessity of conducting checkpointing to avoid excessive checkpointing overhead. Third, to avoid inappropriate runtime CPU clock frequency with low energy utility, a CPU frequency modulator is proposed which adjusts the runtime CPU clock frequency adaptively. Finally, to thrive in ultra-low harvesting power scenarios, a light-weight software paradigm is proposed to help maximize the energy extraction rate of the energy harvester and power regulator bundle. Besides, checkpointing is also optimized for more energy-efficient and light-weight operation

Energy Optimization Efficiency in Wireless Sensor Networks for Forest Fire Detection:: An Innovative Sleep Technique

Wireless Sensor Networks (WSNs) have the potential to play a significant role in forest fire detection and prevention. However, limited resources, such as short battery life pose challenges for the energy efficiency and longevity of WSN-based IoT networks. This paper focused on the energy efficiency aspect and proposed the ECP-LEACH protocol to optimize energy consumption in forest fire detection cases. The proposed protocol consists of two main components: a threshold monitoring module and a sleep scheduling module. The threshold monitoring module continuously monitors energy consumption and triggers sleep mode for nodes surpassing the predetermined threshold. The ECP-LEACH protocol offers a promising solution for improving energy efficiency in WSN-based IoT networks for forest fire detection. By optimizing sleep scheduling and duty cycles, the ECP-LEACH protocol enables significant energy savings and extended network lifetim

Power Analysis and Optimization Techniques for Energy Efficient Computer Systems

Reducing power consumption has become a major challenge in the design and operation of to-day’s computer systems. This chapter describes different techniques addressing this challenge at different levels of system hardware, such as CPU, memory, and internal interconnection network, as well as at different levels of software components, such as compiler, operating system and user applications. These techniques can be broadly categorized into two types: Design time power analysis versus run-time dynamic power management. Mechanisms in the first category use ana-lytical energy models that are integrated into existing simulators to measure the system’s power consumption and thus help engineers to test power-conscious hardware and software during de-sign time. On the other hand, dynamic power management techniques are applied during run-time, and are used to monitor system workload and adapt the system’s behavior dynamically to save energy