Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures最新文献

Session details: SESSION 5 会话详细信息:Session 5

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3257329

K. Censor-Hillel

引用次数: 0

Minimizing Total Weighted Flow Time with Calibrations 最大限度地减少总加权流动时间与校准

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087573

Vincent Chau, Minming Li, Samuel McCauley, Kai Wang

{"title":"Minimizing Total Weighted Flow Time with Calibrations","authors":"Vincent Chau, Minming Li, Samuel McCauley, Kai Wang","doi":"10.1145/3087556.3087573","DOIUrl":"https://doi.org/10.1145/3087556.3087573","url":null,"abstract":"In sensitive applications, machines need to be periodically calibrated to ensure that they run to high standards. Creating an efficient schedule on these machines requires attention to two metrics: ensuring good throughput of the jobs, and ensuring that not too much cost is spent on machine calibration. In this paper we examine flow time as a metric for scheduling with calibrations. While previous papers guaranteed that jobs would meet a certain deadline, we relax that constraint to a tradeoff: we want to balance how long the average job waits with how many costly calibrations we need to perform. One advantage of this metric is that it allows for online schedules (where an algorithm is unaware of a job until it arrives). Thus we give two types of results. We give an efficient offline algorithm which gives the optimal schedule on a single machine for a set of jobs which are known ahead of time. We also give online algorithms which adapt to jobs as they come. Our online algorithms are constant competitive for unweighted jobs on single or multiple machines, and constant-competitive for weighted jobs on a single machine.","PeriodicalId":162994,"journal":{"name":"Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116967536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Brief Announcement: STAR (Space-Time Adaptive and Reductive) Algorithms for Dynamic Programming Recurrences with more than O(1) Dependency 简要公告:具有大于O(1)依赖性的动态规划递归的STAR(时空自适应和简化)算法

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087593

Yuan Tang, Shiyi Wang

{"title":"Brief Announcement: STAR (Space-Time Adaptive and Reductive) Algorithms for Dynamic Programming Recurrences with more than O(1) Dependency","authors":"Yuan Tang, Shiyi Wang","doi":"10.1145/3087556.3087593","DOIUrl":"https://doi.org/10.1145/3087556.3087593","url":null,"abstract":"It's important to hit a space-time balance for a real-world algorithm to achieve high performance on modern shared-memory multi-core and many-core systems. However, a large class of dynamic programs with more than O(1) dependency achieved optimality either in space or time, but not both. In the literature, the problem is known as the fundamental space-time tradeoff. We propose the notion of \"Processor-Adaptiveness.\" In contrast to the prior \"Processor-Awareness\", our approach does not partition statically the problem space to the processor grid, but uses the processor count P to just upper bound the space and cache requirement in a cache-oblivious fashion. In the meantime, our processor-adaptive algorithms enjoy the full benefits of \"dynamic load-balance\", which is a key to achieving satisfactory speedup on a shared-memory system, especially when the problem dimension n is reasonably larger than P. By utilizing the \"busy-leaves\" property of runtime scheduler and a program managed memory pool that combines the advantages of stack and heap, we show that our STAR (Space-Time Adaptive and Reductive) technique can help these dynamic programs to achieve sublinear time bounds while keeping to be asymptotically work-, space-, and cache-optimal. The key achievement of this paper is to obtain the first sublinear O(n3/4 log n) time and optimal O(n3) work GAP algorithm; If we further bound the space and cache requirement of the algorithm to be asymptotically optimal, there will be a factor of P increase in time bound without sacrificing the work bound. If P = o(n1/4 / log n), the time bound stays sublinear and may be a better tradeoff between time and space requirements in practice.","PeriodicalId":162994,"journal":{"name":"Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures","volume":"483 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114279220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Tight Bounds for Clairvoyant Dynamic Bin Packing 透视动态装箱的紧密边界

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087570

Y. Azar, Danny Vainstein

{"title":"Tight Bounds for Clairvoyant Dynamic Bin Packing","authors":"Y. Azar, Danny Vainstein","doi":"10.1145/3087556.3087570","DOIUrl":"https://doi.org/10.1145/3087556.3087570","url":null,"abstract":"In this paper we focus on the Clairvoyant Dynamic Bin Packing (DBP) problem, which extends the classical online bin packing problem in that items arrive and depart over time and the departure time of an item is known upon its arrival. The problem naturally arises when handling cloud-based networks. We focus specifically on the MinUsageTime cost function which aims to minimize the overall usage time of all bins that are opened during the packing process. Earlier work has shown a O(frac{log mu}{log log mu}) upper bound where mu is defined as the ratio between the maximal and minimal durations of all items. We improve the upper bound by giving an O(sqrt{log mu})-competitive algorithm. We then provide a matching lower bound of Omega(sqrt{log mu}) on the competitive ratio of any online algorithm, thus closing the gap with regards to this problem. We then focus on what we call the class of aligned inputs and give a O(log log mu)-competitive algorithm for this case, beating the lower bound of the general case by an exponential factor. Surprisingly enough, the analysis of our algorithm that we present, is closely related to various properties of binary strings.","PeriodicalId":162994,"journal":{"name":"Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures","volume":"2020 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114295575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Brief Announcement: Towards Fault-Tolerant Bin Packing for Online Cloud Resource Allocation 简短公告:面向在线云资源分配的容错装箱

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087596

Chuanyou Li, Xueyan Tang

{"title":"Brief Announcement: Towards Fault-Tolerant Bin Packing for Online Cloud Resource Allocation","authors":"Chuanyou Li, Xueyan Tang","doi":"10.1145/3087556.3087596","DOIUrl":"https://doi.org/10.1145/3087556.3087596","url":null,"abstract":"We consider an online fault-tolerant bin packing problem that models the reliable resource allocation in cloud-based systems. In this problem, any feasible packing algorithm must satisfy an exclusion constraint and a space constraint. The exclusion constraint is generalized from the fault-tolerance requirement and the space constraint comes from the capacity planning. The target of bin packing is to minimize the number of bins used. We first derive a lower bound on the number of bins needed by any feasible packing algorithm. Then we study two heuristic algorithms mirroring and shifting. The mirroring algorithm has a low utilization of the bin capacity. Compared with the mirroring algorithm, the shifting algorithm requires fewer numbers of bins. However, in online packing, the process of opening bins by the shifting algorithm is not smooth. It turns out that even for packing a few items, the shifting algorithm needs to quickly open a large number of bins. We therefore propose a new heuristic algorithm named mixing which can gradually open new bins for incoming items. We prove that the mixing algorithm is feasible and show that it balances the number of bins used and the process of opening bins.","PeriodicalId":162994,"journal":{"name":"Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129353214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Brief Announcement: Using Multi-Level Parallelism and 2-3 Cuckoo Filters for Set Intersection Queries and Sparse Boolean Matrix Multiplication 简要公告:使用多级并行和2-3杜鹃过滤器的集合交集查询和稀疏布尔矩阵乘法

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087599

D. Eppstein, M. Goodrich

引用次数: 1

Brief Announcement: Extending Transactional Memory with Atomic Deferral 简短声明:用原子延迟扩展事务性内存

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087600

Tingzhe Zhou, Victor Luchangco, Michael F. Spear

引用次数: 1

Brief Announcement: Graph Matching in Massive Datasets 简短公告:大规模数据集中的图匹配

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087601

Soheil Behnezhad, M. Derakhshan, Hossein Esfandiari, E. Tan, Hadi Yami

引用次数: 11

Session details: SESSION 8 会话详细信息:Session 8

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3257332

B. Patt-Shamir

引用次数: 0

On Energy Conservation in Data Centers 关于数据中心的节能

Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures Pub Date : 2017-07-24 DOI: 10.1145/3087556.3087560

S. Albers

{"title":"On Energy Conservation in Data Centers","authors":"S. Albers","doi":"10.1145/3087556.3087560","DOIUrl":"https://doi.org/10.1145/3087556.3087560","url":null,"abstract":"We formulate and study an optimization problem that arises in the energy management of data centers and, more generally, multiprocessor environments. Data centers host a large number of heterogeneous servers. Each server has an active state and several standby/sleep states with individual power consumption rates. The demand for computing capacity varies over time. Idle servers may be transitioned to low-power modes so as to rightsize the pool of active servers. The goal is to find a state transition schedule for the servers that minimizes the total energy consumed. On a small scale the same problem arises in multi-core architectures with heterogeneous processors on a chip. One has to determine active and idle periods for the cores so as to guarantee a certain service and minimize the consumed energy. For this power/capacity management problem, we develop two main results. We use the terminology of the data center setting. First, we investigate the scenario that each server has two states, i.e. an active state and a sleep state. We show that an optimal solution, minimizing energy consumption, can be computed in polynomial time by a combinatorial algorithm. The algorithm resorts to a single-commodity min-cost flow computation. Second, we study the general scenario that each server has an active state and multiple standby/sleep states. We devise a tau-approximation algorithm that relies on a two-commodity min-cost flow computation. Here tau is the number of different server types. A data center has a large collection of machines but only a relatively small number of different server architectures. Moreover, in the optimization one can assign servers with comparable energy consumption to the same class. Technically, both of our algorithms involve non-trivial flow modification procedures. In particular, given a fractional two-commodity flow, our algorithm executes advanced rounding and flow packing routines.","PeriodicalId":162994,"journal":{"name":"Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116755308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18