198 research outputs found
Dataflow acceleration of Smith-Waterman with Traceback for high throughput Next Generation Sequencing
Smith-Waterman algorithm is widely adopted bymost popular DNA sequence aligners. The inherent algorithmcomputational intensity and the vast amount of NGS input datait operates on, create a bottleneck in genomic analysis flows forshort-read alignment. FPGA architectures have been extensivelyleveraged to alleviate the problem, each one adopting a differentapproach. In existing solutions, effective co-design of the NGSshort-read alignment still remains an open issue, mainly due tonarrow view on real integration aspects, such as system widecommunication and accelerator call overheads. In this paper, wepropose a dataflow architecture for Smith-Waterman Matrix-filland Traceback alignment stages, to perform short-read alignmenton NGS data. The architectural decision of moving both stages onchip extinguishes the communication overhead, and coupled withradical software restructuring, allows for efficient integration intowidely-used Bowtie2 aligner. This approach delivers×18 speedupover the respective Bowtie2 standalone components, while our co-designed Bowtie2 demonstrates a 35% boost in performance
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Oops: Optimizing operation-mode selection for IoT edge devices
The massive increase of IoT devices and their collected data raises the question of how to analyze all that data. Edge computing provides a suitable compromise, but the question remains: How much processing should be done locally vs. offloaded to other devices? The diverse application requirements and limited resources at the edge extend the challenges.
We propose
Oops
, an optimization framework to adapt the resource management at runtime distributedly. It orchestrates the IoT devices and adapts their operation mode with respect to their constraints and the gateway’s limited shared resources. Oops reduces runtime overhead significantly while increasing user utility compared to state-of-the-art.
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A Partitioning Methodology for Accelerating Applications in Hybrid Reconfigurable Platforms *
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BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations
Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. Approach. In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU
EXA2PRO programming environment:Architecture and applications
The EXA2PRO programming environment will integrate a set of tools and methodologies that will allow to systematically address many exascale computing challenges, including performance, performance portability, programmability, abstraction and reusability, fault tolerance and technical debt. The EXA2PRO tool-chain will enable the efficient deployment of applications in exascale computing systems, by integrating high-level software abstractions that offer performance portability and efficient exploitation of exascale systems' heterogeneity, tools for efficient memory management, optimizations based on trade-offs between various metrics and fault-tolerance support. Hence, by addressing various aspects of productivity challenges, EXA2PRO is expected to have significant impact in the transition to exascale computing, as well as impact from the perspective of applications. The evaluation will be based on 4 applications from 4 different domains that will be deployed in JUELICH supercomputing center. The EXA2PRO will generate exploitable results in the form of a tool-chain that support diverse exascale heterogeneous supercomputing centers and concrete improvements in various exascale computing challenges
Применение метода контрольных возмущений для определения характерных узлов присоединения комплексной нагрузки при расчетах динамической устойчивости
Рассматривается влияние способа замещения комплексной нагрузки на характер электромеханических переходных процессов в электрических системах (ЭС) от действия больших возмущений. Показано, что установить общие рекомендации относительно способа замещения нагрузки в сложных ЭС затруднительно. Предлагается для определения характерных узлов нагрузки, оказывающих существенное влияние на характер динамического перехода, применять известный метод контрольных возмущений. Приводятся результаты сравнительных расчетов с использованием предлагаемой методики
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