14650134
Reducing branch predictor leakage energy by exploiting loops
With the scaling of technology, leakage energy will become the dominant source of energy consumption. Besides cache memories, branch predictors are among the largest on-chip array structures and consume nontrivial leakage energy. This paper proposes two cost-effective loop-based strategies to reduce the branch predictor leakage without impacting prediction accuracy or performance. The loop-based approaches exploit the fact that loops usually only contain a small number of instructions and, hence, even fewer branch instructions while taking a significant fraction of the execution time. Consequently, all the nonactive entries of branch predictors can be placed into the low leakage mode during the loop execution in order to reduce leakage energy. Compiler and circuit supports are discussed to implement the proposed leakage-reduction strategies. Compared to the recently proposed decay-based approach, our experimental results show that the loop-based approach can extract 16.2% more dead time of the branch predictor, on average, leading to more leakage energy savings without impacting the branch prediction accuracy and performance.
8356979
Real-time Accurate Object Detection using Multiple Resolutions
We propose a multi-resolution framework inspired by human visual search for general object detection. Different resolutions are represented using a coarse-to-fine feature hierarchy. During detection, the lower resolution features are initially used to reject the majority of negative windows at relatively low cost, leaving a relatively small number of windows to be processed in higher resolutions. This enables the use of computationally more expensive higher resolution features to achieve high detection accuracy. We applied this framework on Histograms of Oriented Gradient (HOG) features for object detection. Our multi-resolution detector produced better performance for pedestrian detection than state-of-the-art methods (Dalal and Triggs, 2005), and was faster during both training and testing. Testing our method on motorbikes and cars from the VOC database revealed similar improvements in both speed and accuracy, suggesting that our approach is suitable for realtime general object detection applications.
13431767
A compiler approach for reducing data cache energy
Silicon technology advances have made it possible to pack millions of transistors --- switching at high clock speeds --- on a single chip. While these advances bring unprecedented performance to electronic products, they pose difficult power/energy consumption problems. For example, large number of transistors in dense on-chip cache memories consume significant static (leakage) power even if the cache is not used by the current computation. While previous compiler research studied code and data restructuring for improving data cache performance, to our knowledge, there is no compiler-based study that targets data cache leakage power consumption. In this paper, we present code restructuring techniques for array-based and pointer-intensive applications for reducing data cache energy consumption. The idea is to let the compiler to analyze the code and insert instructions that turn off cache lines that keep variables not used by the current computation. This turning off does not destroy contents of a cache line, and waking up the cache line incurs very little overhead. Due to data locality, we find that at a given time only a small portion of the data cache needs to be active; the remaining part can be placed into a leakage-saving mode (state); i.e., they can be turned off. Our preliminary results indicate that the proposed strategy reduces the cache energy consumption significantly. We also show that several compiler optimizations increase the effectiveness of our strategy.
12152152
Interprocedural optimizations for improving data cache performance of array-intensive embedded applications
As datasets processed by embedded processors increase in size and complexity, the management of higher levels of memory hierarchy (e.g., caches) is becoming an important issue. A major limitation of most of the cache locality optimization techniques proposed by previous research is that they handle a single procedure at a time. This prevents compilers from capturing the data access interactions between procedures and may result in poor performance. In this paper, we look at loop and data transformations from a different angle and use them in an interprocedural optimization framework. Employing the call graph representation of a given application, the proposed technique visits each node of this graph twice and uses loop and data transformations in a systematic way for optimizing array layouts whole program wide. Our experimental results show that this interprocedural locality optimization strategy is much more effective than the previous locality-based techniques that handle each procedure in isolation.
12737974
The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search
To investigate how top-down (TD) and bottom-up (BU) information is weighted in the guidance of human search behavior, we manipulated the proportions of BU and TD components in a saliency-based model. The model is biologically plausible and implements an artificial retina and a neuronal population code. The BU component is based on feature-contrast. The TD component is defined by a feature-template match to a stored target representation. We compared the model's behavior at different mixtures of TD and BU components to the eye movement behavior of human observers performing the identical search task. We found that a purely TD model provides a much closer match to human behavior than any mixture model using BU information. Only when biological constraints are removed (e.g., eliminating the retina) did a BU/TD mixture model begin to approximate human behavior.
15072800
Loop-based leakage control for branch predictors
Leakage energy consumption is becoming an important design consideration with the scaling of technology. Besides caches, branch predictors are among the largest on-chip array structures and consume non-trivial leakage energy. This paper proposes two loop-based strategies to reduce the branch predictor leakage without impacting prediction accuracy, which is crucial for achieving high performance. The loop-based approaches exploit the fact that loops usually only contain a small number of instructions and hence fewer branch instructions. Consequently, all the non-active entries of branch predictors can be placed into the low leakage mode during the loop execution for leakage energy savings. Compilers can annotate this information and pass it to the processor for reducing leakage at runtime. Compared to the recently-proposed decay-based approach, our experimental results show that the loop-based approach can extract 16.2% more branch predictor idleness on average, leading to more leakage energy savings without impacting the branch prediction accuracy and performance.
12929858
UWB Spatia - Frequency Channel Characterization
This paper investigates the spatial-frequency channel characterization of ultra-wideband (UWB) wireless communication systems. First, a novel frequency dependent UWB channel model is constructed based on the theory of electromagnetic diffraction mechanism, which causes the field strength to vary with the frequency in each multipath. Then, we build a space-frequency model, which includes spatial characteristics such as angular power spectrum, and physical sampling points in space. The space-frequency model has two special cases (i) discrete multipath model, and (ii) cluster model, which can be readily used to generate channel data for any arbitrary set of sensor locations. The reconstruction results from channel measurements show the accurateness of the novel frequency dependent model, with reconstruction error decreasing by 40%, compared to the traditional Turin model
7006061
Iterative extrapolation algorithm for data reconstruction over sphere
Given limited or incomplete measurement data on a sphere, a new iterative algorithm is proposed on how to extrapolate signal over the whole sphere. The algorithm is based on a priori assumption that the Fourier decomposition of the signal on the sphere has finite degree of spherical harmonic coefficients, that is, the signal is mode limited. The algorithm is a simple iteration involving only the spherical harmonic decomposition. It is proven that the algorithm converges to the original signal over observation region and the convergence rate is lower bounded by the largest eigenvalue of an associated Fredholm integral equation.
1223138
Efficient Continuous HRTF Model Using Data Independent Basis Functions: Experimentally Guided Approach
This paper introduces a continuous functional model for head-related transfer functions (HRTFs) in the horizontal auditory scene. The approach uses a separable representation consisting of a Fourier-Bessel series expansion for the spectral components and a conventional Fourier series expansion for the spatial components. Being independent of the data, these two sets of basis functions remain unchanged for all subjects and measurement setups. Hence, the model can transform an individualized HRTF to a subject specific set of coefficients. A continuous functional model is also developed in the time domain. We show the efficient model performance in approximating experimental measurements by using the HRTF measurements from a KEMAR manikin and the synthetic data from the spherical head model. The statistical results are determined from a 50-subject HRTF data set. We also corroborate the predictive capability of the proposed model. The model has near optimal performance, which can be ascertained by comparison with the standard principle component analysis (PCA) and discrete Karhunen-Loeve expansion (KLE) methods at the measurement points and for a given number of parameters.