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Deconstructing Blockchains: A Comprehensive Survey on Consensus, Membership and StructureAug 22 2019It is no exaggeration to say that since the introduction of Bitcoin, blockchains have become a disruptive technology that has shaken the world. However, the rising popularity of the paradigm has led to a flurry of proposals addressing variations and/or ... More
BRIDGE: Byzantine-resilient Decentralized Gradient DescentAug 21 2019Decentralized optimization techniques are increasingly being used to learn machine learning models from data distributed over multiple locations without gathering the data at any one location. Unfortunately, methods that are designed for faultless networks ... More
Dynamic Scheduling of MPI-based Distributed Deep Learning Training JobsAug 21 2019There is a general trend towards solving problems suited to deep learning with more complex deep learning architectures trained on larger training sets. This requires longer compute times and greater data parallelization or model parallelization. Both ... More
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile ProcessorsAug 21 2019In recent years, convolutional networks have demonstrated unprecedented performance in the image restoration task of super-resolution (SR). SR entails the upscaling of a single low-resolution image in order to meet application-specific image quality demands ... More
Federated Learning: Challenges, Methods, and Future DirectionsAug 21 2019Federated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping data localized. Training in heterogeneous and potentially massive networks introduces novel challenges ... More
Decentralized Federated Learning: A Segmented Gossip ApproachAug 21 2019The emerging concern about data privacy and security has motivated the proposal of federated learning, which allows nodes to only synchronize the locally-trained models instead their own original data. Conventional federated learning architecture, inherited ... More
A sufficient condition for a linear speedup in competitive parallel computingAug 21 2019In competitive parallel computing, the identical copies of a code in a phase of a sequential program are assigned to processor cores and the result of the fastest core is adopted. In the literature, it is reported that a superlinear speedup can be achieved ... More
Securing HPC using Federated AuthenticationAug 20 2019Federated authentication can drastically reduce the overhead of basic account maintenance while simultaneously improving overall system security. Integrating with the user's more frequently used account at their primary organization both provides a better ... More
Eunomia: A Permissionless Parallel Chain Protocol Based on Logical ClockAug 20 2019The emerging parallel chain protocols represent a breakthrough to address the scalability of blockchain. By composing multiple parallel chain instances, the whole systems' throughput can approach the network capacity. How to coordinate different chains' ... More
Towards Effective Device-Aware Federated LearningAug 20 2019With the wealth of information produced by social networks, smartphones, medical or financial applications, speculations have been raised about the sensitivity of such data in terms of users' personal privacy and data security. To address the above issues, ... More
Evacuation of equilateral triangles by mobile agents of limited communication rangeAug 20 2019We consider the problem of evacuating $k \geq 2$ mobile agents from a unit-sided equilateral triangle through an exit located at an unknown location on the perimeter of the triangle. The agents are initially located at the centroid of the triangle and ... More
Numerically robust tetrahedron-based tomographic forward and backward projectors on parallel architecturesAug 19 2019X-ray tomographic reconstruction typically uses voxel basis functions to represent volumetric images. Due to the structure in voxel basis representations, efficient ray-tracing methods exist allowing fast, GPU accelerated implementations. Tetrahedral ... More
Directed Homotopy in Non-Positively Curved SpacesAug 19 2019A semantics of concurrent programs can be given using precubical sets, in order to study (higher) commutations between the actions, thus encoding the "geometry" of the space of possible executions of the program. Here, we study the particular case of ... More
A Computational Model for Tensor Core UnitsAug 19 2019To respond to the need of efficient training and inference of deep neural networks, a pletora of domain-specific hardware architectures have been introduced, such as Google Tensor Processing Units and NVIDIA Tensor Cores. A common feature of these architectures ... More
System Evaluation of the Intel Optane Byte-addressable NVMAug 18 2019Byte-addressable non-volatile memory (NVM) features high density, DRAM comparable performance, and persistence. These characteristics position NVM as a promising new tier in the memory hierarchy. Nevertheless, NVM has asymmetric read and write performance, ... More
The Rise of Blockchain Technology in Agriculture and Food Supply ChainsAug 18 2019Blockchain is an emerging digital technology allowing ubiquitous financial transactions among distributed untrusted parties, without the need of intermediaries such as banks. This article examines the impact of blockchain technology in agriculture and ... More
DMap: A Distributed Blockchain-based Framework for Online Mapping in Smart CityAug 18 2019Smart cities are growing significantly due to the growth of smart connected vehicles and Internet of Things (IoT) where a wide range of devices are connected to share data. Online mapping is one of the fundamental services offered in smart cities which ... More
StreamNet: A DAG System with Streaming Graph ComputingAug 18 2019To achieve high throughput in the POW based blockchain systems, a series of methods has been proposed, and DAG is one of the most active and promising field. We designed and implemented the StreamNet aiming to engineer a scalable and endurable DAG system. ... More
Nakamoto Consensus with Verifiable Delay PuzzleAug 18 2019This technical report summarizes our work-in-progress on a new consensus protocol based on verifiable delay function. First, we introduce the concept of verifiable delay puzzle (VDP), which resembles the hashing puzzle used in the PoW mechanism but can ... More
A Sharp Threshold Phenomenon for the Distributed Complexity of the Lovász Local LemmaAug 17 2019Aug 20 2019The Lov\'{a}sz Local Lemma (LLL) says that, given a set of bad events that depend on the values of some random variables and where each event happens with probability at most $p$ and depends on at most $d$ other events, there is an assignment of the variables ... More
A Sharp Threshold Phenomenon for the Distributed Complexity of the Lovasz Local LemmaAug 17 2019The Lov\'{a}sz Local Lemma (LLL) says that, given a set of bad events that depend on the values of some random variables and where each event happens with probability at most $p$ and depends on at most $d$ other events, there is an assignment of the variables ... More
Report on workflow analysis for specific LAM applicationsAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Report on energy-efficiency evaluation of several NWP model configurationsAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Projections of achievable performance for Weather & Climate Dwarfs, and for entire NWP applications, on hybrid architecturesAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Performance report and optimized implementations of Weather & Climate dwarfs on multi-node systemsAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Performance report and optimized implementation of Weather & Climate Dwarfs on GPU, MIC and Optalysys Optical ProcessorAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Recommendations and specifications for data scope analysis toolsAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Report on the performance portability demonstrated for the relevant Weather & Climate DwarfsAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Additional key features required for different directives based porting approachesAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
A Shift Selection Strategy for Parallel Shift-Invert Spectrum Slicing in Symmetric Self-Consistent Eigenvalue ComputationAug 16 2019The central importance of large scale eigenvalue problems in scientific computation necessitates the development massively parallel algorithms for their solution. Recent advances in dense numerical linear algebra have enabled the routine treatment of ... More
Development of Atlas, a flexible data structure frameworkAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Batch 2: Definition of novel Weather & Climate DwarfsAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Batch 1: Definition of several Weather & Climate DwarfsAug 16 2019This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European ... More
Parallel Computation of Alpha Complex for BiomoleculesAug 16 2019Alpha complex, a subset of the Delaunay triangulation, has been extensively used as the underlying representation for biomolecular structures. We propose a GPU based parallel algorithm for the computation of the alpha complex, which exploits the knowledge ... More
Path-Sensitive Atomic Commit: Local Coordination Avoidance for Distributed Transactions (Technical Report)Aug 16 2019Concurrent objects with asynchronous messaging are an increasingly popular way to structure highly available, high performance, large-scale software systems. To ensure data-consistency and support synchronization between objects such systems often use ... More
stdgpu: Efficient STL-like Data Structures on the GPUAug 16 2019Tremendous advances in parallel computing and graphics hardware opened up several novel real-time GPU applications in the fields of computer vision, computer graphics as well as augmented reality (AR) and virtual reality (VR). Although these applications ... More
Federated Learning with Additional Mechanisms on Clients to Reduce Communication CostsAug 16 2019Federated learning (FL) enables on-device training over distributed networks consisting of a massive amount of modern smart devices, such as smartphones and IoT devices. However, the leading optimization algorithm in such settings, i.e., federated averaging ... More
Distributed Edge Partitioning for Trillion-edge GraphsAug 16 2019We propose Distributed Neighbor Expansion (Distributed NE), a parallel and distributed edge partitioning method that can scale to trillion-edge graphs while providing high partitioning quality. Distributed NE is based on a new heuristic, called parallel ... More
A Reliable IoT-Based Embedded Health Care System for Diabetic PatientsAug 16 2019This paper introduces a reliable health care system for diabetic patients based on the Internet of Things technology. A diabetic health care system with a hardware implementation is presented. The proposed work employs Alaris 8100 infusion pump, Keil ... More
Multitask and Transfer Learning for Autotuning Exascale ApplicationsAug 15 2019Multitask learning and transfer learning have proven to be useful in the field of machine learning when additional knowledge is available to help a prediction task. We aim at deriving methods following these paradigms for use in autotuning, where the ... More
Task Bench: A Parameterized Benchmark for Evaluating Parallel Runtime PerformanceAug 15 2019We present Task Bench, a parameterized benchmark designed to explore the performance of parallel and distributed programming systems under a variety of application scenarios. Task Bench lowers the barrier to benchmarking multiple programming systems by ... More
Distributed Backup Placement in One Round and its Applications to Maximum Matching Approximation and Self-StabilizationAug 15 2019In the distributed backup-placement problem each node of a network has to select one neighbor, such that the maximum number of nodes that make the same selection is minimized. This is a natural relaxation of the perfect matching problem, in which each ... More
CLOTHO: Directed Test Generation for Weakly Consistent Database SystemsAug 15 2019Relational database applications are notoriously difficult to test and debug. Concurrent execution of database transactions may violate complex structural invariants that constraint how changes to the contents of one (shared) table affect the contents ... More
Secure Coded Cooperative Computation at the Heterogeneous Edge against Byzantine AttacksAug 15 2019Edge computing is emerging as a new paradigm to allow processing data at the edge of the network, where data is typically generated and collected, by exploiting multiple devices at the edge collectively. However, offloading tasks to other devices leaves ... More
Resolvable Designs for Speeding up Distributed ComputingAug 14 2019Distributed computing frameworks such as MapReduce are often used to process large computational jobs. They operate by partitioning each job into smaller tasks executed on different servers. The servers also need to exchange intermediate values to complete ... More
Aleph: Efficient Atomic Broadcast in Asynchronous Networks with Byzantine NodesAug 14 2019The spectacular success of Bitcoin and Blockchain Technology in recent years has provided enough evidence that a widespread adoption of a common cryptocurrency system is not merely a distant vision, but a scenario that might come true in the near future. ... More
ClustCrypt: Privacy-Preserving Clustering of Unstructured Big Data in the CloudAug 14 2019Security and confidentiality of big data stored in the cloud are important concerns for many organizations to adopt cloud services. One common approach to address the concerns is client-side encryption where data is encrypted on the client machine before ... More
Fog Robotics: A Summary, Challenges and Future ScopeAug 14 2019Human-robot interaction plays a crucial role to make robots closer to humans. Usually, robots are limited by their own capabilities. Therefore, they utilise Cloud Robotics to enhance their dexterity. Its ability includes the sharing of information such ... More
Constrained Multi-Objective Optimization for Automated Machine LearningAug 14 2019Automated machine learning has gained a lot of attention recently. Building and selecting the right machine learning models is often a multi-objective optimization problem. General purpose machine learning software that simultaneously supports multiple ... More
Serverless Supercomputing: High Performance Function as a Service for ScienceAug 14 2019Growing data volumes and velocities are driving exciting new methods across the sciences in which data analytics and machine learning are increasingly intertwined with research. These new methods require new approaches for scientific computing in which ... More
Least Squares Approximation for a Distributed SystemAug 14 2019In this work we develop a distributed least squares approximation (DLSA) method, which is able to solve a large family of regression problems (e.g., linear regression, logistic regression, Cox's model) on a distributed system. By approximating the local ... More
Meeting QoS of Users in a Edge to Cloud Platform via Optimally Placing Services and Scheduling TasksAug 13 2019This paper considers the problem of service placement and task scheduling on a three-tiered edge-to-cloud platform when user requests must be met by a certain deadline. Time-sensitive applications (e.g., augmented reality, gaming, real-time video analysis) ... More
Exploiting Parallelism Opportunities with Deep Learning FrameworksAug 13 2019State-of-the-art machine learning frameworks support a wide variety of design features to enable a flexible machine learning programming interface and to ease the programmability burden on machine learning developers. Identifying and using a performance-optimal ... More
A Scalable, Portable, and Memory-Efficient Lock-Free FIFO QueueAug 13 2019We present a new lock-free multiple-producer and multiple-consumer (MPMC) FIFO queue design which is scalable and, unlike existing high-performant queues, very memory efficient. Moreover, the design is ABA safe and does not require any external memory ... More
Industrial Control via Application Containers: Migrating from Bare-Metal to IAASAug 13 2019We explore the challenges and opportunities of shifting industrial control software from dedicated hardware to bare-metal servers or cloud computing platforms using off the shelf technologies. In particular, we demonstrate that executing time-critical ... More
Enabling Simulation of High-Dimensional Micro-Macro Biophysical Models through Hybrid CPU and Multi-GPU ParallelismAug 12 2019Micro-macro models provide a powerful tool to study the relationship between microscale mechanisms and emergent macroscopic behavior. However, the detailed microscopic modeling may require tracking and evolving a high-dimensional configuration space at ... More
Cache Optimization for Memory Intensive Workloads on Multi-socket Multi-core serversAug 12 2019Major chip manufacturers have all introduced multicore microprocessors. Multi-socket systems built from these processors are used for running various server applications. Depending on the application that is run on the system, remote memory accesses can ... More
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective OperationsAug 12 2019Load imbalance pervasively exists in distributed deep learning training systems, either caused by the inherent imbalance in learned tasks or by the system itself. Traditional synchronous Stochastic Gradient Descent (SGD) achieves good accuracy for a wide ... More
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective OperationsAug 12 2019Aug 13 2019Load imbalance pervasively exists in distributed deep learning training systems, either caused by the inherent imbalance in learned tasks or by the system itself. Traditional synchronous Stochastic Gradient Descent (SGD) achieves good accuracy for a wide ... More
Shared-Memory Branch-and-Reduce for Multiterminal CutsAug 12 2019We introduce the fastest known exact algorithm~for~the multiterminal cut problem with k terminals. In particular, we engineer existing as well as new data reduction rules. We use the rules within a branch-and-reduce framework and to boost the performance ... More
Shared-Memory Branch-and-Reduce for Multiterminal CutsAug 12 2019Aug 17 2019We introduce the fastest known exact algorithm~for~the multiterminal cut problem with k terminals. In particular, we engineer existing as well as new data reduction rules. We use the rules within a branch-and-reduce framework and to boost the performance ... More
An Adaptive $s$-step Conjugate Gradient Algorithm with Dynamic Basis UpdatingAug 12 2019The adaptive $s$-step CG algorithm is a solver for sparse, symmetric positive definite linear systems designed to reduce the synchronization cost per iteration while still achieving a user-specified accuracy requirement. In this work, we improve the adaptive ... More
Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN)Aug 11 2019Some Deep Neural Networks (DNN) have what we call lanes, or they can be reorganized as such. Lanes are paths in the network which are data-independent and typically learn different features or add resilience to the network. Given their data-independence, ... More
Lightweight and Scalable Particle Tracking and Motion Clustering of 3D Cell TrajectoriesAug 10 2019Aug 14 2019Tracking cell particles in 3D microscopy videos is a challenging task but is of great significance for modeling the motion of cells. Proper characterization of the cell's shape, evolution, and their movement over time is crucial to understanding and modeling ... More
Lightweight and Scalable Particle Tracking and Motion Clustering of 3D Cell TrajectoriesAug 10 2019Tracking cell particles in 3D microscopy videos is a challenging task but is of great significance for modeling the motion of cells. Proper characterization of the cell's shape, evolution, and their movement over time is crucial to understanding and modeling ... More
Edge Computing for User-Centric Secure Search on Cloud-Based Encrypted Big DataAug 10 2019Cloud service providers offer a low-cost and convenient solution to host unstructured data. However, cloud services act as third-party solutions and do not provide control of the data to users. This has raised security and privacy concerns for many organizations ... More
An Empirical Guide to the Behavior and Use of Scalable Persistent MemoryAug 09 2019After nearly a decade of anticipation, scalable nonvolatile memory DIMMs are finally commercially available with the release of Intel's 3D XPoint DIMM. This new nonvolatile DIMM supports byte-granularity accesses with access times on the order of DRAM, ... More
Improved Network Decompositions using Small Messages with Applications on MIS, Neighborhood Covers, and BeyondAug 09 2019Network decompositions, as introduced by Awerbuch, Luby, Goldberg, and Plotkin [FOCS'89], are one of the key algorithmic tools in distributed graph algorithms. We present an improved deterministic distributed algorithm for constructing network decompositions ... More
RCE: An Integration Environment for Engineering and ScienceAug 09 2019We present RCE (Remote Component Environment), an open-source framework developed primarily at DLR (German Aerospace Center) that enables its users to construct and execute multidisciplinary engineering workflows comprising multiple disciplinary tools. ... More
Trade-offs in Distributed Interactive ProofsAug 09 2019The study of interactive proofs in the context of distributed network computing is a novel topic, recently introduced by Kol, Oshman, and Saxena [PODC 2018]. In the spirit of sequential interactive proofs theory, we study the power of distributed interactive ... More
Science needs to rethink how it interacts with big data: Five principles for effective scientific big data systemsAug 09 2019We should be in a golden age of scientific discovery, given that we have more data and more compute power available than ever before. But paradoxically, in many data-driven fields, the eureka moments are becoming more and more rare. Scientists, and the ... More
Efficient Simulation of Fluid Flow and Transport in Heterogeneous Media Using Graphics Processing Units (GPUs)Aug 09 2019Networks of interconnected resistors, springs and beams, or pores are standard models of studying scalar and vector transport processes in heterogeneous materials and media, such as fluid flow in porous media, and conduction, deformations, and electric ... More
Managing the Complexity of Processing Financial Data at Scale -- an Experience ReportAug 08 2019Financial markets are extremely data-driven and regulated. Participants rely on notifications about significant events and background information that meet their requirements regarding timeliness, accuracy, and completeness. As one of Europe's leading ... More
Privatization-Safe Transactional Memories (Extended Version)Aug 08 2019Transactional memory (TM) facilitates the development of concurrent applications by letting the programmer designate certain code blocks as atomic. Programmers using a TM often would like to access the same data both inside and outside transactions, and ... More
From Piz Daint to the Stars: Simulation of Stellar Mergers using High-Level AbstractionsAug 08 2019We study the simulation of stellar mergers, which requires complex simulations with high computational demands. We have developed Octo-Tiger, a finite volume grid-based hydrodynamics simulation code with Adaptive Mesh Refinement which is unique in conserving ... More
From Piz Daint to the Stars: Simulation of Stellar Mergers using High-Level AbstractionsAug 08 2019Aug 09 2019We study the simulation of stellar mergers, which requires complex simulations with high computational demands. We have developed Octo-Tiger, a finite volume grid-based hydrodynamics simulation code with Adaptive Mesh Refinement which is unique in conserving ... More
TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep LearningAug 08 2019Recent studies from several hyperscalars pinpoint to embedding layers as the most memory-intensive deep learning (DL) algorithm being deployed in today's datacenters. This paper addresses the memory capacity and bandwidth challenges of embedding layers ... More
Small Cuts and Connectivity Certificates: A Fault Tolerant ApproachAug 08 2019We revisit classical connectivity problems in the CONGEST model of distributed computing. By using techniques from fault tolerant network design, we show improved constructions, some of which are even "local" (i.e., with $\widetilde{O}(1)$ rounds) for ... More
Byzantine Approximate Agreement on GraphsAug 07 2019Consider a distributed system with $n$ processors out of which $f$ can be Byzantine faulty. In the approximate agreement task, each processor $i$ receives an input value $x_i$ and has to decide on an output value $y_i$ such that - the output values are ... More
Parallel Finger Search StructuresAug 07 2019Aug 09 2019In this paper we present two versions of a parallel finger structure FS on p processors that supports searches, insertions and deletions, and has a finger at each end. This is to our knowledge the first implementation of a parallel search structure that ... More
Parallel Finger Search StructuresAug 07 2019In this paper we present two versions of a parallel finger structure FS on p processors that supports searches, insertions and deletions, and has a fixed number of movable fingers. This is to our knowledge the first implementation of a parallel search ... More
A Generic Efficient Biased Optimizer for Consensus ProtocolsAug 07 2019Consensus is one of the most fundamental distributed computing problems. In particular, it serves as a building block in many replication based fault-tolerant systems and in particular in multiple recent blockchain solutions. Depending on its exact variant ... More
Near-Memory Computing: Past, Present, and FutureAug 07 2019The conventional approach of moving data to the CPU for computation has become a significant performance bottleneck for emerging scale-out data-intensive applications due to their limited data reuse. At the same time, the advancement in 3D integration ... More
Redundancy Scheduling in Systems with Bi-Modal Job Service Time DistributionAug 07 2019Queuing systems with redundant requests have drawn great attention because of their promise to reduce the job completion time and its variability. Despite a large body of work on this topic, we are still far from fully understanding the benefits of redundancy ... More
Motivating Workers in Federated Learning: A Stackelberg Game PerspectiveAug 06 2019Due to the large size of the training data, distributed learning approaches such as federated learning have gained attention recently. However, the convergence rate of distributed learning suffers from heterogeneous worker performance. In this paper, ... More
LUCE: A Blockchain Solution for monitoring data License accoUntability and CompliancEAug 06 2019In this paper we present our preliminary work on monitoring data License accoUntability and CompliancE (LUCE). LUCE is a blockchain platform solution designed to stimulate data sharing and reuse, by facilitating compliance with licensing terms. The platform ... More
Wait-Free Universality of Consensus in the Infinite Arrival ModelAug 06 2019In classical asynchronous distributed systems composed of a fixed number n of processes where some proportion may fail by crashing, many objects do not have a wait-free linearizable implementation (e.g. stacks, queues, etc.). It has been proved that consensus ... More
Edge AIBench: Towards Comprehensive End-to-end Edge Computing BenchmarkingAug 06 2019In edge computing scenarios, the distribution of data and collaboration of workloads on different layers are serious concerns for performance, privacy, and security issues. So for edge computing benchmarking, we must take an end-to-end view, considering ... More
Blockchain Consensus Formation while Solving Optimization ProblemsAug 06 2019This paper proposes a new decentralized consensus protocol for a blockchain.
The Capacity of Smartphone Peer-to-Peer NetworksAug 05 2019Aug 07 2019We study three capacity problems in the mobile telephone model, a network abstraction that models the peer-to-peer communication capabilities implemented in most commodity smartphone operating systems. The capacity of a network expresses how much sustained ... More
The Capacity of Smartphone Peer-to-Peer NetworksAug 05 2019We study three capacity problems in the mobile telephone model, a network abstraction that models the peer-to-peer communication capabilities implemented in most commodity smartphone operating systems. The capacity of a network expresses how much sustained ... More
Scalable Byzantine Reliable Broadcast (Extended Version)Aug 05 2019Byzantine reliable broadcast is a powerful primitive that allows a set of processes to agree on a message from a designated sender, even if some processes (including the sender) are Byzantine. Existing broadcast protocols for this setting scale poorly, ... More
Data Aggregation In The Astroparticle Physics Distributed Data StorageAug 05 2019German-Russian Astroparticle Data Life Cycle Initiative is an international project whose aim is to develop a distributed data storage system that aggregates data from the storage systems of different astroparticle experiments. The prototype of such a ... More
Repair Pipelining for Erasure-Coded Storage: Algorithms and EvaluationAug 05 2019We propose repair pipelining, a technique that speeds up the repair performance in general erasure-coded storage. By pipelining the repair of failed data in small-size units across storage nodes, repair pipelining reduces the single-block repair time ... More
EdgeMORE: Improving Resource Allocation with Multiple Options from TenantsAug 05 2019Under the paradigm of Edge Computing (EC), a Network Operator (NO) deploys computational resources at the network edge and let third-party services run on top of them. Besides the clear advantages for Service Providers (SPs) and final users thanks to ... More
Revisiting consensus protocols through wait-free parallelizationAug 05 2019The recent surge of blockchain systems has renewed the interest in traditional Byzantine fault-tolerant consensus protocols. Many such consensus protocols have a primary-backup design in which an assigned replica, the primary, is responsible for coordinating ... More
Revisiting consensus protocols through wait-free parallelizationAug 05 2019Aug 06 2019The recent surge of blockchain systems has renewed the interest in traditional Byzantine fault-tolerant consensus protocols. Many such consensus protocols have a primary-backup design in which an assigned replica, the primary, is responsible for coordinating ... More
The fault-tolerant cluster-sending problemAug 05 2019The development of fault-tolerant distributed systems that can tolerate Byzantine behavior has traditionally been focused on consensus protocols, which support fully-replicated designs. For the development of more sophisticated high-performance Byzantine ... More
GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPUAug 04 2019High-performance implementations of graph algorithms are challenging to implement on new parallel hardware such as GPUs, because of three challenges: (1) difficulty of coming up with graph building blocks, (2) load imbalance on parallel hardware, and ... More
GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPUAug 04 2019Aug 09 2019High-performance implementations of graph algorithms are challenging to implement on new parallel hardware such as GPUs, because of three challenges: (1) difficulty of coming up with graph building blocks, (2) load imbalance on parallel hardware, and ... More