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Neural recording is one of the most noteworthy technologies in today's world, where large amount of recorded neural signal over prolonged duration consumes hefty time and energy for data transmission. During the past decade, the discrete cosine transform (DCT) has been used for data compression in bio-medical application due to its high energy efficiency. In this paper, a multiplication-free integer...
Using multiple streams can improve the overall system performance by mitigating the data transfer overhead on heterogeneous systems. Prior work focuses a lot on GPUs but little is known about the performance impact on (Intel Xeon) Phi. In this work, we apply multiple streams into six real-world applications on Phi. We then systematically evaluate the performance benefits of using multiple streams...
The presence of multiplicative noise in synthetic aperture radar (SAR) images makes segmentation and classification difficult to handle. Although a fuzzy C-means (FCM) algorithm and its variants (e.g., the FCM_S, the fast generalized FCM, the fuzzy local information C-means, etc.) can achieve satisfactory segmentation results and are robust to Gaussian noise, uniform noise, and salt and pepper noise,...
As a fast on-chip SRAM managed by software (the application and/or compiler), Scratchpad Memory (SPM) is widely used in many fields. This paper presents a Simple Scalar-based multi-level SPM memory hierarchy architecture simulator Sim-spm. We simulate the hardware of the multi-level SPM memory hierarchy successfully by extending Sim-outorder, which is an out-of-order simulator from Simple Scalar....
OpenMP is a widely used parallel programming model on traditional multi-core processors. Generally, OpenMP is used to develop fine-grained parallelism through a multi-thread model. Stream programming model is a new kind of parallel programming model for stream architectures. OpenMP bears a resemblance to the stream programming model at some level. The transformation between the two models has attracted...
In recent years, heterogeneous parallel system have become a focus research area in high performance computing field. Generally, in a heterogeneous parallel system, CPU provides the basic computing environment and special purpose accelerator (GPU in this paper) provides high computing performance. However, the overall performance of the system is prone to be limited by the data communication between...
This research visualizes the spatial patterns of diagnosed colon and lung cancer mortalities across the New York State. Kernel density analysis was applied to visualize the spatial patterns of old industrial sites across the state. Geographically Weighted Regression (GWR) was applied to model the possible pollution impact of old industrial sites on colon and lung cancer incidents. GWR is a local spatial...
Graphic Processing Unit (GPU), with many light-weight data-parallel cores, can provide substantial parallel computing power to accelerate several general purpose applications. Both the AMD and NVIDIA corps provide their specific high performance GPUs and software platforms. As the floating-point computing capacity increases continually, the problem of ``memory-wall'' becomes more serious, especially...
Graphic Processing Unit (GPU), with many light-weight data-parallel cores, can provide substantial parallel computational power to accelerate general purpose applications. But the powerful computing capacity could not be fully utilized for memory-intensive applications, which are limited by off-chip memory bandwidth and latency. Stencil computation has abundant parallelism and low computational intensity...
Strip-mining is a critical optimization for improving the effectiveness of memory hierarchy of Imagine. In this paper, we present an efficient compiler algorithm for selecting the optimal strip size to minimize the execution time of stream programs. First, we build a graceful analytical model that characterizes the effect of strip size on key performance factors. Then, we design a novel algorithm...
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