scholarly journals Implementation of Scientific Computing Applications on the Cell Broadband Engine

2009 ◽  
Vol 17 (1-2) ◽  
pp. 135-151 ◽  
Author(s):  
Guochun Shi ◽  
Volodymyr V. Kindratenko ◽  
Ivan S. Ufimtsev ◽  
Todd J. Martinez ◽  
James C. Phillips ◽  
...  
Keyword(s):  
High Performance ◽  
Scientific Computing ◽  
Lessons Learned ◽  
Optimization Techniques ◽  
Cell Processor ◽  
Intrinsic Properties ◽  
Cell Broadband Engine ◽  
Performance Improvements ◽  
Cell Architecture ◽  
Practical Recommendations

The Cell Broadband Engine architecture is a revolutionary processor architecture well suited for many scientific codes. This paper reports on an effort to implement several traditional high-performance scientific computing applications on the Cell Broadband Engine processor, including molecular dynamics, quantum chromodynamics and quantum chemistry codes. The paper discusses data and code restructuring strategies necessary to adapt the applications to the intrinsic properties of the Cell processor and demonstrates performance improvements achieved on the Cell architecture. It concludes with the lessons learned and provides practical recommendations on optimization techniques that are believed to be most appropriate.

scholarly journals A Python-based optimization framework for high-performance genomics

2020 ◽  
Author(s):  
Ariya Shajii ◽  
Ibrahim Numanagić ◽  
Alexander T. Leighton ◽  
Haley Greenyer ◽  
Saman Amarasinghe ◽  
...  
Keyword(s):  
High Performance ◽  
Optimization Techniques ◽  
Computational Genomics ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Low Level ◽  
Performance Improvements ◽  
Optimization Framework ◽  
Novice Programmer ◽  
High Level

AbstractExponentially-growing next-generation sequencing data requires high-performance tools and algorithms. Nevertheless, the implementation of high-performance computational genomics software is inaccessible to many scientists because it requires extensive knowledge of low-level software optimization techniques, forcing scientists to resort to high-level software alternatives that are less efficient. Here, we introduce Seq—a Python-based optimization framework that combines the power and usability of high-level languages like Python with the performance of low-level languages like C or C++. Seq allows for shorter, simpler code, is readily usable by a novice programmer, and obtains significant performance improvements over existing languages and frameworks. We showcase and evaluate Seq by implementing seven standard, widely-used applications from all stages of the genomics analysis pipeline, including genome index construction, finding maximal exact matches, long-read alignment and haplotype phasing, and demonstrate its implementations are up to an order of magnitude faster than existing hand-optimized implementations, with just a fraction of the code. By enabling researchers of all backgrounds to easily implement high-performance analysis tools, Seq further opens the door to the democratization and scalability of computational genomics.

Multicore Surprises: Lessons Learned from Optimizing Sweep3D on the Cell Broadband Engine

2007 ◽  
Author(s):  
Fabrizio Petrini ◽  
Gordon Fossum ◽  
Juan Fernandez ◽  
Ana Lucia Varbanescu ◽  
Mike Kistler ◽  
...  
Keyword(s):  
Lessons Learned ◽  
Cell Broadband Engine

scholarly journals Compiler-directed scratchpad memory data transfer optimization for multithreaded applications on a heterogeneous many-core architecture

2021 ◽  
Author(s):  
Xiaohan Tao ◽  
Jianmin Pang ◽  
Jinlong Xu ◽  
Yu Zhu
Keyword(s):  
Energy Consumption ◽  
High Performance ◽  
Scientific Computing ◽  
Data Transfer ◽  
Performance Model ◽  
Experimental Result ◽  
Transfer Model ◽  
Scratchpad Memory ◽  
On Chip ◽  
Many Core

AbstractThe heterogeneous many-core architecture plays an important role in the fields of high-performance computing and scientific computing. It uses accelerator cores with on-chip memories to improve performance and reduce energy consumption. Scratchpad memory (SPM) is a kind of fast on-chip memory with lower energy consumption compared with a hardware cache. However, data transfer between SPM and off-chip memory can be managed only by a programmer or compiler. In this paper, we propose a compiler-directed multithreaded SPM data transfer model (MSDTM) to optimize the process of data transfer in a heterogeneous many-core architecture. We use compile-time analysis to classify data accesses, check dependences and determine the allocation of data transfer operations. We further present the data transfer performance model to derive the optimal granularity of data transfer and select the most profitable data transfer strategy. We implement the proposed MSDTM on the GCC complier and evaluate it on Sunway TaihuLight with selected test cases from benchmarks and scientific computing applications. The experimental result shows that the proposed MSDTM improves the application execution time by 5.49$$\times$$ × and achieves an energy saving of 5.16$$\times$$ × on average.

Learnings from the Field Implementation of a Novel Ultra-High Performance Concrete Beam End Repair on a Corroded Steel Girder Bridge in Connecticut

2021 ◽  
pp. 036119812110041
Author(s):  
Alexandra Hain ◽  
Arash E. Zaghi
Keyword(s):  
High Performance ◽  
High Performance Concrete ◽  
Implementation Process ◽  
Lessons Learned ◽  
Load Path ◽  
Ultra High Performance Concrete ◽  
Steel Girder Bridge ◽  
Aging Steel ◽  
Girder Bridge ◽  
The University

Corrosion at steel beam ends is one of the most pressing challenges in the maintenance of aging bridges. To tackle this challenge, the Connecticut Department of Transportation (DOT) has partnered with the University of Connecticut to develop a repair method that benefits from the superior mechanical and durability characteristics of ultra-high performance concrete (UHPC) material. The repair involves welding shear studs to the intact portions of the web and encasing the beam end with UHPC. This provides an alternate load path for bearing forces that bypasses the corroded regions of the beam. The structural viability of the repair has been extensively proven through small- and full-scale experiments and comprehensive finite element simulations. Connecticut DOT implemented the repair for the first time in the field on a heavily trafficked four-span bridge in 2019. The UHPC beam end repair was chosen because of the access constraints and geometric complexities of the bridge that limited the viable repair options. Four of the repaired beam ends were fully instrumented to collect data on the performance of the repaired locations before casting, during curing, and for approximately 6 months following the application of the repair. This paper provides an overview of the successful repair implementation and presents the lessons learned during construction. Select data from the monitored beam ends are presented. It is expected that this information will provide engineers with a better understanding of the repair implementation process, and thus provide an additional repair option for states to enhance the safety of aging steel bridges.

Fräsen partikelverstärkter Titanmatrix-Verbundwerkstoffe*/Milling of particle-reinforced titanium metal matrix composites

2017 ◽  
Vol 107 (04) ◽  
pp. 301-305
Author(s):  
E. Prof. Uhlmann ◽  
F. Kaulfersch
Keyword(s):  
High Performance ◽  
High Wear Resistance ◽  
Tool Geometry ◽  
Matrix Composites ◽  
Titanium Matrix ◽  
Titanium Matrix Composites ◽  
Performance Improvements ◽  
Significant Performance ◽  
High Temperature Components ◽  
Process Strategy

Partikelverstärkte Titanmatrix-Verbundwerkstoffe erlauben erhebliche Leistungssteigerungen im Bereich hochtemperaturbeanspruchter Struktur- und Funktionsbauteile. Die durch die Partikelverstärkung gesteigerte Verschleißbeständigkeit, Festigkeit und Härte bedeuten eine große Herausforderung an die spanende Bearbeitung derartiger Hochleistungswerkstoffe. Mittels Zerspanuntersuchungen beim Fräsen konnten unter Variation der Werkzeuggeometrie, der Schneidstoffe und der Prozessstrategie Parameterbeiche identifiziert werden, mit denen die prozesssichere Zerspanung partikelverstärkter Titanmatrix-Verbundwerkstoffe möglich ist.   Particle-reinforced titanium matrix composites ensure significant performance improvements of structural and functional high-temperature components. However, the high wear resistance, toughness and hardness due to particle reinforcement is a major challenge in machining these high performance materials. By conducting milling experiments with a variation of tool geometry, cutting material and process strategy, process parameters could be identified that enable efficient machining of particle-reinforced titanium matrix composites.

scholarly journals Communication and Networking Technologies for UAVs: A Survey

2020 ◽  
Author(s):  
Chathuranga M. Wijerathna Basnayaka ◽  
Dushantha Nalin K. Jayakody
Keyword(s):  
Research Work ◽  
Communication Technologies ◽  
Lessons Learned ◽  
Optimization Techniques ◽  
Network Architectures ◽  
Vehicle Communication ◽  
Work Related ◽  
Aerial Vehicle ◽  
Networking Technologies ◽  
Communication Methods

With the advancement in drone technology, in just a few years, drones will be assisting humans in every domain. But there are many challenges to be tackled, communication being the chief one. This paper aims at providing insights into the latest UAV (Unmanned Aerial Vehicle) communication technologies through investigation of suitable task modules, antennas, resource handling platforms, and network architectures. Additionally, we explore techniques such as machine learning and path planning to enhance existing drone communication methods. Encryption and optimization techniques for ensuring long−lasting and secure communications, as well as for power management, are discussed. Moreover, applications of UAV networks for different contextual uses ranging from navigation to surveillance, URLLC (Ultra-reliable and low−latency communications), edge computing and work related to artificial intelligence are examined. In particular, the intricate interplay between UAV, advanced cellular communication, and internet of things constitutes one of the focal points of this paper. The survey encompasses lessons learned, insights, challenges, open issues, and future directions in UAV communications. Our literature review reveals the need for more research work on drone−to−drone and drone−to−device communications.

scholarly journals Improving speed of models for improved real-world decision-making

2021 ◽  
Author(s):  
Jason Thompson ◽  
Haifeng Zhao ◽  
Sachith Seneviratne ◽  
Rohan Byrne ◽  
Rajith Vidanaarachichi ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Real World ◽  
High Performance ◽  
Time Pressure ◽  
Practical Importance ◽  
Model Development ◽  
Sudden Onset ◽  
Health Crisis ◽  
Performance Improvements ◽  
Performance Computing

The sudden onset of the COVID-19 global health crisis and as-sociated economic and social fall-out has highlighted the im-portance of speed in modeling emergency scenarios so that ro-bust, reliable evidence can be placed in policy and decision-makers’ hands as swiftly as possible. For computational social scientists who are building complex policy models but who lack ready access to high-performance computing facilities, such time-pressure can hinder effective engagement. Popular and ac-cessible agent-based modeling platforms such as NetLogo can be fast to develop, but slow to run when exploring broad param-eter spaces on individual workstations. However, while deploy-ment on high-performance computing (HPC) clusters can achieve marked performance improvements, transferring models from workstations to HPC clusters can also be a technically challenging and time-consuming task. In this paper we present a set of generic templates that can be used and adapted by NetLogo users who have access to HPC clusters but require ad-ditional support for deploying their models on such infrastruc-ture. We show that model run-time speed improvements of be-tween 200x and 400x over desktop machines are possible using 1) a benchmark ‘wolf-sheep predation’ model in addition to 2) an example drawn from our own work modeling the spread of COVID-19 in Victoria, Australia. We describe how a focus on improving model speed is non-trivial for model development and discuss its practical importance for improved policy and de-cision-making in the real world. We provide all associated doc-umentation in a linked git repository.

scholarly journals Preliminary Sailplane Design Using MDO And Multi-Fidelity Analysis

2021 ◽  
Author(s):  
Chris V. Pilcher
Keyword(s):  
Multidisciplinary Design Optimization ◽  
High Performance ◽  
Vortex Lattice ◽  
Optimization Techniques ◽  
Multidisciplinary Design ◽  
Preliminary Design ◽  
Adaptive Meshing ◽  
Analysis Methods ◽  
And Performance ◽  
Modern Optimization

A multidisciplinary design optimization (MDO) strategy for the preliminary design of a sailplane has been developed. The proposed approach applies MDO techniques and multi-fidelity analysis methods which have seen successful use in many aerospace design applications. A customized genetic algorithm (GA) was developed to control the sailplane optimization that included aerodynamics/stability, structures/weights and balance and, performance/airworthiness disciplinary analysis modules. An adaptive meshing routine was developed to allow for accurate modeling of the aero structural couplinginvolved in wing design, which included a finite element method (FEM) structural solver along with a vortex lattice aerodynamics solver. Empirical equations were used to evaluate basic sailplane performance and airworthiness requirements. This research yielded an optimum design that correlated well with an existing high performance sailplane. The results of this thesis suggest that preliminary sailplane design is a well suited application for modern optimization techniques when coupled with, multi-fidelity analysis methods.

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