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Youshan Miao, Wentao Han, Kaiwei Li, Ming Wu, Fan Yang, Lidong Zhou, Vijayan Prabhakaran, Enhong Chen, and Wenguang Chen

Temporal graphs that capture graph changes over time are attracting increasing interest from research communities, for functions such as understanding temporal characteristics of social interactions on a time-evolving social graph. ImmortalGraph is a storage and execution engine designed and optimized specifically for temporal graphs. Locality is at the center of ImmortalGraph’s design: temporal graphs are carefully laid out in both persistent storage and memory, taking into account data locality in...

Publication details
Date: 1 December 2015
Type: Article
Publisher: ACM – Association for Computing Machinery
Hitesh Ballani, Paolo Costa, Christos Gkantsidis, Matthew P. Grosvenor, Thomas Karagiannis, Lazaros Koromilas, and Greg O'Shea
Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Virajith Jalaparti, Peter Bodik, Ishai Menache, Sriram Rao, Konstantin Makarychev, and Matt Caesar
Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: ACM SIGCOMM
Paolo Costa, Hitesh Ballani, Kaveh Razavi, and Ian Kash

Rack-scale computers, comprising a large number of micro-servers connected by a direct-connect topology, are poised to replace servers as the building block in data centers. We focus on the problem of routing and congestion control across the rack's network, and find that high path diversity in rack topologies, in combination with workload diversity across it, means that traditional solutions are inadequate.

We present R2C2, a network stack for rack-scale computers providing flexible and...

Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: KDD
Kalin Ovtcharov, Olatunji Ruwase, Joo-Young Kim, Jeremy Fowers, Karin Strauss, and Eric Chung
Publication details
Date: 1 August 2015
Type: Proceedings
Publisher: HOTCHIPS
Publication details
Date: 1 July 2015
Type: Inproceeding
Publisher: USENIX
Publication details
Date: 1 July 2015
Type: Inproceeding
Publisher: USENIX – Advanced Computing Systems Association
Konstantinos Karanasos, Sriram Rao, Carlo Curino, Chris Douglas, Kishore Chaliparambil, Giovanni Fumarola, Solom Heddaya, Raghu Ramakrishnan, and Sarvesh Sakalanaga

Datacenter-scale computing for analytics workloads is increasingly common. High operational costs force heterogeneous applications to share cluster resources for achieving economy of scale. Scheduling such large and diverse workloads is inherently hard, and existing approaches tackle this in two alternative ways: 1) centralized solutions offer strict, secure enforcement of scheduling invariants (e.g., fairness, capacity) for heterogeneous applications, 2) distributed solutions offer...

Publication details
Date: 1 July 2015
Type: Inproceeding
Publisher: USENIX – Advanced Computing Systems Association
Dan Alistarh, Rati Glasvili, and Milan Vojnovic

Population protocols, roughly defined as systems consisting of large numbers of simple identical agents, interacting at random and updating their state following simple rules, are an important research topic at the intersection of distributed computing and biology. One of the fundamental tasks that a population protocol may solve is majority: each node starts in one of two states; the goal is for all nodes to reach a correct consensus on which of the two states was initially the majority....

Publication details
Date: 1 July 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Dan Alistarh, Thomas Sauerwald, and Milan Vojnovic

In this work, we consider the following random process, motivated by the analysis of lock-free concurrent algorithms under high memory contention. In each round, a new scheduling step is allocated to one of $n$ threads, according to a distribution $\vect{p} = (p_1, p_2, \ldots, p_n)$, where thread $i$ is scheduled with probability $p_i$. When some thread first reaches a set threshold of executed steps, it registers a \emph{win}, completing its current operation, and resets its step count to $1$. At...

Publication details
Date: 1 July 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Jian Huang, Anirudh Badam, Moinuddin K. Qureshi, and Karsten Schwann

Applications can map data on SSDs into virtual memory to transparently scale beyond DRAM capacity, permitting them to leverage high SSD capacities with few code changes. Obtaining good performance for memory-mapped SSD content, however, is hard because the virtual memory layer, the file system and the flash translation layer (FTL) perform address translations, sanity and permission checks independently from each other. We introduce FlashMap, an SSD interface that is
optimized for memory-mapped...

Publication details
Date: 13 June 2015
Type: Inproceeding
Publisher: ACM/IEEE
Xi Yang, Stephen M. Blackburn, and Kathryn S. McKinley

Developers and architects spend a lot of time trying to understand and eliminate performance problems. Unfortunately, the root causes of many problems occur at a fine granularity that existing continuous profiling and direct measurement approaches cannot observe. This paper presents the design and implementation of SHIM, a continuous profiler that samples at resolutions as fine as 15 cycles; three to five orders of magnitude finer than current continuous profilers. SHIM’s...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM/IEEE International Symposium on Computer Architecture (ISCA)
Luo Mai, Chuntao Hong, and Paolo Costa

To cope with the ever growing availability of training data, there have been several proposals to scale machine learning computation beyond a single server and distribute it across a server cluster. While this enables significantly reducing the training time, the observed speed up is often limited by the communication bottlenecks.

To address this, we designed Mercury, a host-based stack that optimizes network communication in distributed machine learning systems. This is achieved through a...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: USENIX – Advanced Computing Systems Association
ishai menache and mohit singh

Modern software applications and services operate nowadays on top of large clusters and datacenters. To reduce the underlying infrastructure cost and increase utilization, different services share the same physical resources (e.g., CPU, bandwidth, I/O, memory). Consequently, the cluster provider often has to decide in real-time how to allocate resources in overbooked systems, taking into account the different characteristics and requirements of users. In this paper, we consider an important problem...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Vivek Seshadri, Gennady Pekhimenko, Olatunji Ruwase, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry, and Trishul Chilimbi
Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ISCA
Vasileios Karakostas, Jayneel Gandhi, Furkan Ayar, Adrián Cristal, Mark D. Hill, Kathryn S. McKinley, Mario Nemirovsky, Michael M. Swift, and Osman Ünsal

Page-based virtual memory improves programmer productivity, security, and memory utilization, but incurs performance overheads due to costly page table walks after TLB misses. This overhead can reach 50% for modern workloads that access increasingly vast memory with stagnating TLB sizes.

To reduce the overhead of virtual memory, this paper proposes Redundant Memory Mappings (RMM), which leverage ranges of pages and provides an efficient, alternative representation...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM/IEEE International Symposium on Computer Architecture (ISCA)
Chen Liu, Xiaojiang Chen, Dingyi Fang, Dan Xu, Zhanyong Tang, and Chieh-Jan Mike Liang
Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Jiansong Zhang, Jin Zhang, Kun Tan, Lin Yang, Yongguang Zhang, and Qian Zhang
Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM Mobihoc 2015
Bo Zong, Christos Gkantsidis, and Milan Vojnovic

We study the problem of placing streaming queries into servers. Unlike previous work, we focus on queries that consume events of relative low rates, each computed in a single server (i.e. no scaling out per query). However, we need to place a very large and dynamic number of queries in relatively few servers. Our focus is motivated by the need to support a platform for hosting end-user streaming queries that may come from a variety of applications, such as the Cortana personal assistant.

The...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Philip A. Bernstein, Sudipto Das, Bailu Ding, and Markus Pilman

Scaling-out a database system typically requires partitioning the database across multiple servers. If applications do not partition perfectly, then transactions accessing multiple partitions end up being distributed, which has well-known scalability challenges. To address them, we describe a high-performance transaction mechanism that uses optimistic concurrency control on a multi-versioned tree-structured database stored in a shared log. The system scales out by adding servers, without partitioning...

Publication details
Date: 31 May 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Rayman Preet Singh, Chenguang Shen, Amar Phanishayee, Aman Kansal, and Ratul Mahajan

The proliferation of connected sensing devices (or Internet of Things) can in theory enable a range of applications that make rich inferences about users and their environment. But in practice developing such applications today is arduous because they are constructed as monolithic silos, tightly coupled to sensing devices, and must implement all data sensing and inference logic, even as devices move or are temporarily disconnected. We present Beam, a framework and runtime for distributed...

Publication details
Date: 18 May 2015
Type: Inproceeding
Publisher: USENIX
Jacob R. Lorch, Andrew Baumann, Lisa Glendenning, Dutch T. Meyer, and Andrew Warfield

Many services need to survive machine failures, but designing and deploying fault-tolerant services can be difficult and error-prone. In this work, we present Tardigrade, a system that deploys an existing, unmodified binary as a fault-tolerant service. Tardigrade replicates the service on several machines so that it continues running even when some of them fail. Yet, it keeps the service states synchronized so clients see strongly consistent results. To achieve this efficiently, we use lightweight...

Publication details
Date: 4 May 2015
Type: Inproceeding
Publisher: USENIX – Advanced Computing Systems Association
Jeremy Fowers, Joo-Young Kim, Doug Burger, and Scott Hauck

Data compression techniques have been the subject of intense study over the past several decades due to exponential increases in the quantity of data stored and transmitted by computer systems. Compression algorithms are traditionally forced to make tradeoffs between throughput and compression quality (the ratio of original file size to compressed file size). FPGAs represent a compelling substrate for streaming applications such as data compression thanks to their capacity for deep pipelines and custom...

Publication details
Date: 4 May 2015
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Hucheng Zhou, Jian-Guang Lou, Hongyu Zhang, Haibo Lin, Haoxiang Lin, and Tingting Qin

Big Data computing platform has evolved to be a multi-tenant service. The service quality matters because system failure or performance slowdown could adversely affect business and user experience. There is few study in literature on service quality issues of production Big Data computing platform. In this paper, we present an empirical study on the service quality issues of Microsoft ProductA, which is a company-wide multi-tenant Big Data computing platform, serving thousands of customers from hundreds...

Publication details
Date: 1 May 2015
Type: Inproceeding
Publisher: ICSE SEIP
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