130,672 research outputs found
Modeling of thermally induced skew variations in clock distribution network
No full textClock distribution network is sensitive to large thermal gradients on the die as the performance of both clock buffers and interconnects are affected by temperature. A robust clock network design relies on the accurate analysis of clock skew subject to temperature variations. In this work, we address the problem of thermally induced clock skew modeling in nanometer CMOS technologies. The complex thermal behavior of both buffers and interconnects are taken into account. In addition, our characterization of the temperature effect on buffers and interconnects provides valuable insight to designers about the potential impact of thermal variations on clock networks. The use of industrial standard data format in the interface allows our tool to be easily integrated into existing design flow
Automated Segmentation of Cells with IHC Membrane Staining
No full textThis study presents a fully automated membrane segmentation technique for immunohistochemical tissue images with membrane staining, which is a critical task in computerized immunohistochemistry (IHC). Membrane segmentation is particularly tricky in immunohistochemical tissue images because the cellular membranes are visible only in the stained tracts of the cell, while the unstained tracts are not visible. Our automated method provides accurate segmentation of the cellular membranes in the stained tracts and reconstructs the approximate location of the unstained tracts using nuclear membranes as a spatial reference. Accurate cell-by-cell membrane segmentation allows per cell morphological analysis and quantification of the target membrane proteins that is fundamental in several medical applications such as cancer characterization and classification, personalized therapy design, and for any other applications requiring cell morphology characterization. Experimental results on real datasets from different anatomical locations demonstrate the wide applicability and high accuracy of our approach in the context of IHC analysi
Automated segmentation of tissue images for computerized IHC analysis
No full textThis paper presents two automated methods for the segmentation ofimmunohistochemical tissue images that overcome the limitations of themanual approach aswell as of the existing computerized techniques. The first independent method, based on unsupervised color clustering, recognizes automatically the target cancerous areas in the specimen and disregards the stroma; the second method, based on colors separation and morphological processing, exploits automated segmentation of the nuclear membranes of the cancerous cells. Extensive experimental results on real tissue images demonstrate the accuracy of our techniques compared to manual segmentations; additional experiments show that our techniques are more effective in immunohistochemical images than popular approaches based on supervised learning or active contours. The proposed procedure can be exploited for any applications that require tissues and cells exploration and to perform reliable and standardized measures of the activity of specific proteins involved in multi-factorial genetic pathologie
Hardware-Assisted Data Compression for Energy Minimization in Systems with Embedded Processors
No full textIn this paper, we suggest hardware-assisted data compression as a tool for reducing energy consumption of core-based embedded systems. We propose a novel and efficient architecture for on-the-fly data compression and decompression whose field of operation is the cache-to-memory path. Uncompressed cache lines are compressed before they are written back to main memory, and decompressed when cache refills take place. We explore two classes of compression methods, profile-driven and differential, since they are characterized by compact HW implementations, and we compare their performance to those provided by some state-of-the-art compression methods (e.g., we have considered a few variants of the Lempel-Ziv encoder). We present experimental results about memory traffic and energy consumption in the cache-to-memory path of a core-based system running standard benchmark programs. The achieved average energy savings range from 4.2% to 35.2%, depending on the selected compression algorith
Memory Energy Minimization by Data Compression: Algorithms, Architectures and Implementation
No full textHardware Implementation of Data Compression Algorithms for Memory Energy Optimization
No full textThis paper describes implementation details of a hardware compression and decompression unit (CDU) for optimizing energy consumption in processor-based systems. Many algorithms for data compression (i.e., profile-driven, adaptive, differential) have been introduced in [1, 2]. In all cases, data compression and decompression are performed on-the-fly on the cache-to-memory path: Uncompressed cache lines are compressed before they are written back to main memory, and decompressed when cache refills occur. This paper completes and extends the contributions of [1, 2] by providing evidence on the feasibility of the proposed compression architectures by specifically addressing hardware implementation issues. CDU design is targeted towards energy minimization in the cache- bus-memory subsystem with a strict constraint on performance. As a result, average memory energy reductions evaluated on several benchmark programs are around 24%, at no performance penalty
Power-Optimal RTL Arithmetic Unit Soft-Macro Selection Strategy for Leakage-Sensitive Technologies
No full textWith the advent of nanoscale technologies, developing power efficient ASICs increasingly requires consideration of static power. An effective approach to make RTL synthesis algorithms and tools leakage-aware consists of the smart inference of RTL macros based on design constraints and optimization directives. This involves exploring the new trade-offs spanned by the design of RTL functional units, as an effect of the features of nanoscale technologies and ofthe power optimizations performed by commercial synthesis tools. This work explores these new trade-offs and proves that making RTL macro selection strategies aware of them results in power savings as high as 43%
- …
