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Accelerating the BPMax Algorithm for RNA-RNA Interaction

Chiranjeb Mondal, Sanjay Rajopadhye
2021 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)  
We do this with a polyhedral code generation tool, AL P H AZ, which takes user-specified mapping directives and automatically generates optimized C code that enhances parallelism and locality.  ...  We achieve 100 GFLOPS, which is about a fourth of our platform's peak theoretical single-precision performance for max-plus computation.  ...  I am also grateful to him for accepting me as a student, spending his precious time with me, and guiding me through the basics of high-performance computing and polyhedral compilation.  ... 
doi:10.1109/ipdpsw52791.2021.00042 fatcat:2vvuozzyerg27fzxcz53xmywiy

Analytical Cost Metrics : Days of Future Past [article]

Nirmal Prajapati, Sanjay Rajopadhye, Hristo Djidjev
2018 arXiv   pre-print
With Moore's law driving the evolution of hardware platforms towards exascale, the dominant performance metric (time efficiency) has now expanded to also incorporate power/energy efficiency.  ...  The architectures are constantly evolving making the current performance optimizing strategies less applicable and new strategies to be invented.  ...  Such a codesign approach will help speed up the research work and the chip design process.  ... 
arXiv:1802.01957v1 fatcat:r6lajnt75zb4xahkznt5gb4wx4

An optimization-based algorithm for job shop scheduling

Jihua Wang, Peter B Luh, Xing Zhao, Jinlin Wang
1997 Sadhana (Bangalore)  
By iteratively solving these subproblems and updating the Lagrangian multipliers at the high level, near-optimal schedules are obtained with a lower bound provided as a byproduct.  ...  In this paper, near-optimal solution methodologies for job shop scheduling are examined. The problem is formulated as integer optimization with a "separable" structure.  ...  It is also shown in Table 3b that the schedule obtained at iteration 400 has better performance than the schedule at iteration 1.  ... 
doi:10.1007/bf02744491 fatcat:7dtlwr37tzdphdyplhmzgvvchm

Some thoughts on combinatorial optimisation

M.H. Bjorndal, A. Caprara, P.I. Cowling, F. Della Croce, H. Lourenço, F. Malucelli, A.J. Orman, D. Pisinger, C. Rego, J.J. Salazar
1995 European Journal of Operational Research  
Several issues are considered and discussed with emphasis on a selected number of techniques: heuristics and polyhedral approaches, and problems: knapsack, quadratic 0-1 programming, machine scheduling  ...  Although, in principle, the optimal solution to such a finite problem can be found by a simple enumeration, in practice this task is frequently impossible, especially for practical problems of realistic  ...  Many people believe that the core of polyhedral combinatorics is finding facets, but in most cases the focus is on finding good inequalities and thus speeding up the algorithm.  ... 
doi:10.1016/0377-2217(95)00005-b fatcat:7qg7ztgc6jaifc55d2w367n6hi

An Effective Subgradient Method for Scheduling a Steelmaking-Continuous Casting Process

Kun Mao, Quan-Ke Pan, Tianyou Chai, Peter B. Luh
2015 IEEE Transactions on Automation Science and Engineering  
The approaches can also be applied to other similar production scheduling problems. Index Terms-Hybrid flowshop, Lagrangian relaxation, manufacturing system, scheduling, subgradient optimization.  ...  However, there are two deficiencies in this approach: its empirical termination criteria, such as maximal iteration number or running time, which make it difficult to find a golden rule for various problems  ...  Reference [29] developed a unit-specific event-based continuous-time mixed-integer linear optimization model for the SCC scheduling problem.  ... 
doi:10.1109/tase.2014.2332511 fatcat:akmwlwbj2bg57ni7rupzb4wmme

Global optimality bounds for the placement of control valves in water supply networks

Filippo Pecci, Edo Abraham, Ivan Stoianov
2018 Optimization and Engineering  
in water supply network models.  ...  The branch and bound algorithm converges to good quality feasible solutions in most instances, with bounds on the optimality gap that are comparable to the level of parameter uncertainty usually experienced  ...  Acknowledgements The authors thank the anonymous reviewers for their helpful comments and suggestions, and for their valuable advice on the formulation of the polyhedral relaxations described in Appendix  ... 
doi:10.1007/s11081-018-9412-7 fatcat:5hcr6r2esrcnnm3rzx5likef74

Democratizing Domain-Specific Computing [article]

Yuze Chi, Weikang Qiao, Atefeh Sohrabizadeh, Jie Wang, Jason Cong
2022 arXiv   pre-print
An important question is whether typical software developers can design and implement their own customized DSAs, with affordability and efficiency, to accelerate their applications.  ...  In the past few years, domain-specific accelerators (DSAs), such as Google's Tensor Processing Units, have shown to offer significant performance and energy efficiency over general-purpose CPUs.  ...  Employing a model can speed up the DSE process since we can assess each point in milliseconds instead of several minutes to even hours.  ... 
arXiv:2209.02951v1 fatcat:hgkj6ixohrgwdnwipikcqyyeoa

Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation [article]

Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
2020 arXiv   pre-print
Experimentation with real hardware shows that Chameleon provides 4.45x speed up in optimization time over AutoTVM, while also improving inference time of the modern deep networks by 5.6%.  ...  As such, we devise a solution that can learn to quickly adapt to a previously unseen design space for code optimization, both accelerating the search and improving the output performance.  ...  of inference speed with a given hardware satisfies the given constraints.  ... 
arXiv:2001.08743v1 fatcat:we2zi5q3mvc4hezbcou2kvrleu

TerraNeo—Mantle Convection Beyond a Trillion Degrees of Freedom [chapter]

Simon Bauer, Hans-Peter Bunge, Daniel Drzisga, Siavash Ghelichkhan, Markus Huber, Nils Kohl, Marcus Mohr, Ulrich Rüde, Dominik Thönnes, Barbara Wohlmuth
2020 Lecture Notes in Computational Science and Engineering  
In TerraNeo the hierarchical hybrid grids paradigm was employed to demonstrate that scalability can be achieved when solving the Stokes system with more than ten trillion (1.1 · 10 13 ) degrees of freedom  ...  This contribution reports on the TerraNeo project which delivered novel matrix-free geometric multigrid solvers for the Stokes system that forms the core of mantle convection models.  ...  The model helped to design the new computational kernels by identifying performance bottlenecks and guiding subsequent performance optimization steps.  ... 
doi:10.1007/978-3-030-47956-5_19 fatcat:4jhueyv5qrhfdkmpfxxv5lsmqa

Global optimization advances in Mixed-Integer Nonlinear Programming, MINLP, and Constrained Derivative-Free Optimization, CDFO

Fani Boukouvala, Ruth Misener, Christodoulos A. Floudas
2016 European Journal of Operational Research  
Both research areas have experienced rapid growth, with a common aim to solve a wide range of real-world problems.  ...  This manuscript reviews recent advances in deterministic global optimization for Mixed-Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free Optimization (CDFO).  ...  Jones (2001) compares the performance of kriging-based surrogate models to quadratic non-interpolating models for global-search optimization, while Viana et al. (2013) develop approaches using multiple  ... 
doi:10.1016/j.ejor.2015.12.018 fatcat:jwe7b7ivrzhrjbttdl74eff2pe

Navigation in multiobjective optimization methods

Richard Allmendinger, Matthias Ehrgott, Xavier Gandibleux, Martin Josef Geiger, Kathrin Klamroth, Mariano Luque
2016 Journal of Multi-Criteria Decision Analysis  
the first approach, referred to as navigation, towards a common understanding of search and decision making strategies to identify the mostpreferred solution among the Pareto set for a multiobjective optimization  ...  KEY WORDS: Multiobjective optimization, multiple criteria decision making, preference learning, navigation Definition 1.1 (Navigation) Navigation is the interactive procedure of traversing through a set  ...  Acknowledgement This paper is a product of discussions initiated in the Dagstuhl Seminar 12041: Learning in Multiobjective Optimization. The authors acknowledge gratefully Prof.  ... 
doi:10.1002/mcda.1599 fatcat:4tvr3dj5xfdxhpaat7apmhkh4q

Solving 0-1 knapsack problem by greedy degree and expectation efficiency

Jianhui Lv, Xingwei Wang, Min Huang, Hui Cheng, Fuliang Li
2016 Applied Soft Computing  
and production scheduling.  ...  Due to its NP-hardness, lots of impressive research work has been performed on many variants of the problem.  ...  And then, both dynamic and static expectation efficiency models need to be modified to increase the convergence speed of the optimal solution.  ... 
doi:10.1016/j.asoc.2015.11.045 fatcat:wjnkdab2tvd67ajl4v37jipg54

Polyhedral Relaxations for Optimal Pump Scheduling of Potable Water Distribution Networks [article]

Byron Tasseff, Russell Bent, Carleton Coffrin, Clayton Barrows, Devon Sigler, Jonathan Stickel, Ahmed S. Zamzam, Yang Liu, Pascal Van Hentenryck
2022 arXiv   pre-print
The classic pump scheduling or Optimal Water Flow (OWF) problem for water distribution networks (WDNs) minimizes the cost of power consumption for a given WDN over a fixed time horizon.  ...  The evaluation suggests that our relaxation improvements, model strengthening techniques, and a thoughtfully selected polyhedral relaxation partitioning scheme can substantially improve OWF primal and  ...  Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.  ... 
arXiv:2208.03551v1 fatcat:lfvr7uhqszesxldwkdh4gv7e4q

Chaotic Random Opposition-Based Learning and Cauchy Mutation Improved Moth-Flame Optimization Algorithm for Intelligent Route Planning of Multiple UAVs

Mingxi Ma, Jun Wu, Yue Shi, Longfei Yue, Cheng Yang, Xuyi Chen
2022 IEEE Access  
Experiments show that It generates a random extended tree by randomly spreading BSO algorithm speeds up iterative convergence and reduces from the root node.  ...  Compared with the traditional route planning methods, although the intelligent optimization algorithm has stronger applicability and optimization performance, it also has the problem of poor convergence  ... 
doi:10.1109/access.2022.3172710 fatcat:tufscmvtsrfc5mtmv3uhcq62ke

Runtime pointer disambiguation

Péricles Alves, Fabian Gruber, Johannes Doerfert, Alexandros Lamprineas, Tobias Grosser, Fabrice Rastello, Fernando Magno Quintão Pereira
2015 SIGPLAN notices  
To optimize code effectively, compilers must deal with memory dependencies.  ...  The result of this precision is code quality: the binaries we generate are 10% faster than those that Polly-LLVM produces without our optimization, at the -O3 optimization level of LLVM.  ...  We have been able to achieve a speed up of 11.3% across all the benchmarks.  ... 
doi:10.1145/2858965.2814285 fatcat:2xsekwcm4rbcdlnta62w4bxl4i
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