Alleviation of Data Timing Channels in Normalized/Subnormal Floating Point Multiplier

Author(s):  
Senthil Pitchai ◽  
VE. Jayanthi

Floating point (FP) multiplication goes down in the scientific application when it sustains the subnormal inputs either in the implementation of software or hardware. Any high-level language executes the FP instructions in the graphics processing unit (GPU) and floating-point unit (FPU) for supporting the normalized numbers alone. In FP multiplication, execution times for normalized and subnormal numbers are not equal. Execution time variations create unintentional delay and data timing channels (DTCs). A circuit is proposed for floating-point multiplication to minimize the unintentional delay for the holistic support of subnormal numbers. In this proposed four-path FP multiplication, the circuit produces the four types of output in four paths having different delays for all cases of input combination. These four paths are establishing the DTCs. A maximum delay path is taken into account to combine and equalize the four paths into a single output path. Two levels of the control circuit combine the four paths to a single path for reducing the DTC effect. To evaluate the performance after path equalization, the proposed FP multiplier is implemented in Stratix-IV and Cyclone-IV FPGAs with a delay of 57.25 and 82.82 ns, respectively. Here, eight pipeline stages reduce the delay and improve the operating speed of the entire circuit. Stage delay and operating speed for this FP multiplier in both FPGA implementations are 12.44 and 16.86[Formula: see text]ns, and 153.19 and 116.78[Formula: see text]MHz, respectively.

2019 ◽  
Vol 20 (20) ◽  
pp. 5158 ◽  
Author(s):  
Meng Liang ◽  
Yuhang Fu ◽  
Ruibo Gao ◽  
Qiaoqiao Wang ◽  
Junlan Nie

Molecular visualization is often challenged with rendering of large molecular structures in real time. The key to LOD (level-of-detail), a classical technology, lies in designing a series of hierarchical abstractions of protein. In the paper, we improved the smoothness of transition for these abstractions by constructing a complete binary tree of a protein. In order to reduce the degree of expansion of the geometric model corresponding to the high level of abstraction, we introduced minimum ellipsoidal enveloping and some post-processing techniques. At the same time, a simple, ellipsoid drawing method based on graphics processing unit (GPU) is used that can guarantee that the drawing speed is not lower than the existing sphere-drawing method. Finally, we evaluated the rendering performance and effect on series of molecules with different scales. The post-processing techniques applied, diffuse shading and contours, further conceal the expansion problem and highlight the surface details.


2007 ◽  
Author(s):  
Fredrick H. Rothganger ◽  
Kurt W. Larson ◽  
Antonio Ignacio Gonzales ◽  
Daniel S. Myers

2021 ◽  
Vol 22 (10) ◽  
pp. 5212
Author(s):  
Andrzej Bak

A key question confronting computational chemists concerns the preferable ligand geometry that fits complementarily into the receptor pocket. Typically, the postulated ‘bioactive’ 3D ligand conformation is constructed as a ‘sophisticated guess’ (unnecessarily geometry-optimized) mirroring the pharmacophore hypothesis—sometimes based on an erroneous prerequisite. Hence, 4D-QSAR scheme and its ‘dialects’ have been practically implemented as higher level of model abstraction that allows the examination of the multiple molecular conformation, orientation and protonation representation, respectively. Nearly a quarter of a century has passed since the eminent work of Hopfinger appeared on the stage; therefore the natural question occurs whether 4D-QSAR approach is still appealing to the scientific community? With no intention to be comprehensive, a review of the current state of art in the field of receptor-independent (RI) and receptor-dependent (RD) 4D-QSAR methodology is provided with a brief examination of the ‘mainstream’ algorithms. In fact, a myriad of 4D-QSAR methods have been implemented and applied practically for a diverse range of molecules. It seems that, 4D-QSAR approach has been experiencing a promising renaissance of interests that might be fuelled by the rising power of the graphics processing unit (GPU) clusters applied to full-atom MD-based simulations of the protein-ligand complexes.


2021 ◽  
Vol 20 (3) ◽  
pp. 1-22
Author(s):  
David Langerman ◽  
Alan George

High-resolution, low-latency apps in computer vision are ubiquitous in today’s world of mixed-reality devices. These innovations provide a platform that can leverage the improving technology of depth sensors and embedded accelerators to enable higher-resolution, lower-latency processing for 3D scenes using depth-upsampling algorithms. This research demonstrates that filter-based upsampling algorithms are feasible for mixed-reality apps using low-power hardware accelerators. The authors parallelized and evaluated a depth-upsampling algorithm on two different devices: a reconfigurable-logic FPGA embedded within a low-power SoC; and a fixed-logic embedded graphics processing unit. We demonstrate that both accelerators can meet the real-time requirements of 11 ms latency for mixed-reality apps. 1


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