Narayanan Vijaykrishnan

The design and use of simplepower: a cycle-accurate energy estimation tool

In this paper, we presen t the design and use of a comprehensiv e framework, SimplePower, for ev aluating the effect of high-level algorithmic, architectural, and compilation trade-offs on energy. An execution-driven, cycle-accurate RT lev el energy estimation tool that uses transition sensitive energy models forms the cornerstone of this framework. SimplePower also pro vides the energy consumed in the memory system and on-chip buses using analytical energy models. We presen t the use of SimplePower to evaluate the impact of a new selective gated pipeline register optimization, a high-level data transformation and a pow er-conscious post compilation optimization (register relabeling) on the datapath, memory and on-chip bus energy, respectively. We find that these three optimizations reduce the energy by 18-36% in the datapath, 62% in the memory system and 12% in the instruction cache data bus, respectively.

Energy-driven integrated hardware-software optimizations using SimplePower

With the emergence of a plethora of embedded and portable applications, energy dissipation has joined throughput, area, and accuracy/precision as a major design constraint. Thus, designers must be concerned with both optimizing and estimating the energy consumption of circuits, architectures, and software. Most of the research in energy optimization and/or estimation has focused on single components of the system and has not looked across the interacting spectrum of the hardware and software. The novelty of our new energy estimation framework, SimplePower, is that it evaluates the energy considering the system as a whole rather than just as a sum of parts, and that it concurrently supports both compiler and architectural experimentation. We present the design and use of the SimplePower framework that includes a transition-sensitive, cycle-accurate datapath energy model that interfaces with analytical and transition sensitive energy models for the memory and bus subsystems, respectively. We analyzed the energy consumption of ten codes from the multidimensional array domain, a domain that is important for embedded video and signal processing systems, after applying different compiler and architectural optimizations. Our experiments demonstrate that early estimates from the SimplePower energy estimation framework can help identify the system energy hotspots and enable architects and compiler designers to focus their efforts on these areas.

Dynamic management of scratch-pad memory space

Optimizations aimed at improving the efficiency of on-chip memories are extremely important. We propose a compiler-controlled dynamic on-chip scratch-pad memory (SPM) management framework that uses both loop and data transformations. Experimental results obtained using a generic cost model indicate significant reductions in data transfer activity between SPM and off-chip memory.

A low latency router supporting adaptivity for on-chip interconnects

The increased deployment of system-on-chip designs has drawn attention to the limitations of on-chip interconnects. As a potential solution to these limitations, networks-on-chip (NoC) have been proposed. The NoC routing algorithm significantly influences the performance and energy consumption of the chip. We propose a router architecture which utilizes adaptive routing while maintaining low latency. The two-stage pipelined architecture uses look ahead routing, speculative allocation, and optimal output path selection concurrently. The routing algorithm benefits from congestion-aware flow control, making better routing decisions. We simulate and evaluate the proposed architecture in terms of network latency and energy consumption. Our results indicate that the architecture is effective in balancing the performance and energy of NoC designs.

Reducing leakage energy in FPGAs using region-constrained placement

FPGAs are being increasingly used in a wide variety of applications. While power optimization has been only of secondary importance in many FPGA applications, growing importance of leakage in FPGAs designed in 90nm and below makes it imperative to treat power optimization as a first class citizen. In this paper, we propose a leakage-saving technique for FPGAs that involves dividing the FPGA fabric into small regions and switching on/off the power supply to each region using a sleep transistor in order to conserve leakage energy. Specifically, the regions not used by the placed design are supply gated. Next, we present a new placement strategy to increase the number of regions that can be supply gated. Finally, the supply gating technique is extended to exploit idleness in different parts of the same design during different time periods. Our experiments with different region sizes using various commercial and academic designs indicate that the proposed optimization outperforms conventional placement, and reduces leakage power consumption significantly.

Exploring Fault-Tolerant Network-on-Chip Architectures

The advent of deep sub-micron technology has exacerbated reliability issues in on-chip interconnects. In particular, single event upsets, such as soft errors, and hard faults are rapidly becoming a force to be reckoned with. This spiraling trend highlights the importance of detailed analysis of these reliability hazards and the incorporation of comprehensive protection measures into all network-on-chip (NoC) designs. In this paper, we examine the impact of transient failures on the reliability of on-chip interconnects and develop comprehensive counter-measures to either prevent or recover from them. In this regard, we propose several novel schemes to remedy various kinds of soft error symptoms, while keeping area and power overhead at a minimum. Our proposed solutions are architected to fully exploit the available infrastructures in an NoC and enable versatile reuse of valuable resources. The effectiveness of the proposed techniques has been validated using a cycle-accurate simulator

DRAM energy management using software and hardware directed power mode control

While there have been several studies and proposals for energy conservation for CPUs and peripherals, energy optimization techniques for selective operating mode control of DRAMs have not been fully explored. It has been shown that as much as 90% of overall system energy (excluding I/O) is consumed by the DRAM modules, serving as a good candidate for energy optimizations. Further; DRAM technology has also matured to provide several low energy operating modes (power modes), making it an opportunistic moment to conduct studies exploring the potential benefits of mode control techniques. This paper conducts an in-depth investigation of software and hardware techniques to avail of the DRAM mode control capabilities at a module granularity for energy savings.

Using complete machine simulation for software power estimation: the SoftWatt approach

Power dissipation has become one of the most critical factors for the continued development of both high-end and low-end computer systems. We present a complete system power simulator, called SoftWatt, that models the CPU, memory hierarchy, and a low-power disk subsystem and quantifies the power behavior of both the application and operating system. This tool, built on top of the SimOS infrastructure, uses validated analytical energy models to identify the power hotspots in the system components, capture relative contributions of the user and kernel code to the system power profile, identify the power-hungry operating system services and characterize the variance in kernel power profile with respect to workload. Our results using Spec JVM98 benchmark suite emphasize the importance of complete system simulation to understand the power impact of architecture and operating system on application execution.

Fault tolerant algorithms for network-on-chip interconnect

As technology scales, fault tolerance is becoming a key concern in on-chip communication. Consequently, this work examines fault tolerant communication algorithms for use in the NoC domain. Two different flooding algorithms and a random walk algorithm are investigated. We show that the flood-based fault tolerant algorithms have an exceedingly high communication overhead. We find that the redundant random walk algorithm offers significantly reduced overhead while maintaining useful levels of fault tolerance. We then compare the implementation costs of these algorithms, both in terms of area as well as in energy consumption, and show that the flooding algorithms consume an order of magnitude more energy per message transmitted.

Interconnect and Thermal-aware Floorplanning for 3D Microprocessors

Interconnects are becoming an increasing problem from both performance and power consumption perspective in future technology nodes. The introduction of 3D chip architectures, with their intrinsic capability of reducing wire length, is one of the promising solutions to mitigate the interconnect problem. While interconnect power consumption reduces due to the adoption of 3D designs, the stacking of multiple active layers leads to higher power densities. Thus, high peak temperatures are of major concern in 3D designs. Consequently, we present a thermal-aware floorplanner for 3D architectures. In contrast to most prior work, our floorplanner considers the interconnect power consumption in exploring a thermal-aware floorplan. Our results show that excluding interconnect power can result in peak temperatures being underestimated by as much as 15degC in 90nm technology. Finally, we demonstrate that our floorplanner is effective in lowering peak temperatures using a microprocessor design and four MCNC designs as benchmarks