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.
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.
15801995
Data space oriented scheduling in embedded systems
With the widespread use of embedded devices such as PDAs, printers, game machines, cellular telephones, achieving high performance demands an optimized operating system (OS) that can take full advantage of the underlying hardware components. This paper presents a locality conscious process scheduling strategy for embedded environments. The objective of our scheduling strategy is to maximize reuse in the data cache. It achieves this by restructuring the process codes based on data sharing patterns between processes.
32452076
Replica Victim Caching to Improve Reliability of In-Cache Replication
Soft error conscious cache design is a necessity for reliable computing. ECC or parity-based integrity checking techniques in use today either compromise performance for reliability or vice versa. The recently-proposed ICR (In-Cache Replication) scheme can enhance data reliability with minimal impact on performance, however, it can only exploit a limited space for replication and thus cannot solve the conflicts between the replicas and the primary data without compromising either performance or reliability. This paper proposes to add a small cache, called replica victim cache, to solve this dilemma effectively. Our experimental results show that a replica victim cache of 4 entries can increase reliability of L1 data caches 21.7% more than ICR without impacting performance, and the area overhead is within 10%.
61988520
Exploiting VLIW schedule slacks for dynamic and leakage energy reduction
The mobile computing device market is projected to grow to 16.8 million units in 2004, representing an average annual growth rate of 28% over the five year forecast period. This brings the technologies that optimize system energy to the forefront. As circuits continue to scale in future, it would be important to optimize both leakage and dynamic energy. Effective optimization of leakage and dynamic energy consumption requires a vertical integration of techniques spanning from circuit to software levels. Schedule stacks in codes executing in VLIW architectures present an opportunity for such an integration. In this paper, we present compiler-directed techniques that take advantage of schedule slacks to optimize leakage and dynamic energy consumption. The proposed techniques have been incorporated into a cycle accurate simulator using parameters extracted from circuit level simulation. Our results show that a unified scheme that uses both dynamic and leakage energy reduction techniques is effective in reducing energy consumption.
9935868
Reducing instruction cache energy consumption using a compiler-based strategy
Excessive power consumption is widely considered as a major impediment to designing future microprocessors. With the continued scaling down of threshold voltages, the power consumed due to leaky memory cells in on-chip caches will constitute a significant portion of the processor's power budget. This work focuses on reducing the leakage energy consumed in the instruction cache using a compiler-directed approach.We present and analyze two compiler-based strategies termed as conservative and optimistic. The conservative approach does not put a cache line into a low leakage mode until it is certain that the current instruction in it is dead. On the other hand, the optimistic approach places a cache line in low leakage mode if it detects that the next access to the instruction will occur only after a long gap. We evaluate different optimization alternatives by combining the compiler strategies with state-preserving and state-destroying leakage control mechanisms. We also evaluate the sensitivity of these optimizations to different high-level compiler transformations, energy parameters, and soft errors.
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.
16445226
Modal expansion of HRTFs: Continuous representation in frequency-range-angle
This paper proposes a continuous HRTF representation in both 3D spatial and frequency domains. The method is based on the acoustic reciprocity principle and a modal expansion of the wave equation solution to represent the HRTF variations with different variables in separate basis functions. The derived spatial basis modes can achieve HRTF near-field and far-field representation in one formulation. The HRTF frequency components are expanded using Fourier Spherical Bessel series for compact representation. The proposed model can be used to reconstruct HRTFs at any arbitrary position in space and at any frequency point from a finite number of measurements. Analytical simulated and measured HRTFs from a KEMAR are used to validate the model.
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