Simplifying Distributed System Development

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Publications associées (31)

System Support for Efficient Replication in Distributed Systems

Dragos-Adrian Seredinschi

Current online applications, such as search engines, social networks, or file sharing services, execute across a distributed network of machines. They provide non-stop services to their users despite failures in the underlying network. To achieve such a hi ...

EPFL2019

Fully-Asynchronous Cache-Efficient Simulation of Detailed Neural Networks

Felix Schürmann, Michael Lee Hines

Modern asynchronous runtime systems allow the re-thinking of large-scale scientific applications. With the example of a simulator of morphologically detailed neural networks, we show how detaching from the commonly used bulk-synchronous parallel (BSP) exec ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Asynchronous Branch-Paralle Simulation of Detailed Neuron Models

Felix Schürmann, Michael Lee Hines

Simulations of electrical activity of networks of morphologically detailed neuron models allow for a better understanding of the brain. State-of-the-art simulations describe the dynamics of ionic currents and biochemical processes within branching topologi ...

2019

Secured Routines: Language-based Construction of Trusted Execution Environments

Adrien Ghosn, Edouard Bugnion, James Richard Larus

Trusted Execution Environments (TEEs), such as Intel SGX enclaves, use hardware to ensure the confidentiality and integrity of operations on sensitive data. While the technology is available on many processors, the complexity of its programming model and i ...

USENIX ASSOC2019

Fast General Distributed Transactions with Opacity

Aleksandar Dragojevic, Stanko Novakovic, Georgios Chatzopoulos

Transactions can simplify distributed applications by hiding data distribution, concurrency, and failures from the application developer. Ideally the developer would see the abstraction of a single large machine that runs transactions sequentially and neve ...

ASSOC COMPUTING MACHINERY2019

Exploiting Flow Graph of System of ODEs to Accelerate the Simulation of Biologically-Detailed Neural Networks

Felix Schürmann, Michael Lee Hines, Bruno Ricardo Da Cunha Magalhães

Exposing parallelism in scientific applications has become a core requirement for efficiently running on modern distributed multicore SIMD compute architectures. The granularity of parallelism that can be attained is a key determinant for the achievable ac ...

IEEE2019

Scaling Out Bioinformatics in the Data Center

Sam David Whitlock

Whole Genome Sequencing is a process in the field of bioinformatics that transforms biological samples of DNA into an electronic dataset of genetic bases. The process consists of two sequential components. First, the laboratory process of sequencing transf ...

EPFL2019

Scalable Synchronization in Shared-Memory Systems: Extrapolating, Adapting, Tuning

Georgios Chatzopoulos

As hardware evolves, so do the needs of applications. To increase the performance of an application, there exist two well-known approaches. These are scaling up an application, using a larger multi-core platform, or scaling out, by distributing work to mul ...

EPFL2018

Spatial: A Language and Compiler for Application Accelerators

Christos Kozyrakis, Yunqi Zhang

Industry is increasingly turning to reconfigurable architectures like FPGAs and CGRAs for improved performance and energy efficiency. Unfortunately, adoption of these architectures has been limited by their programming models. HDLs lack abstractions for pr ...

ASSOC COMPUTING MACHINERY2018

A Programming Model and Foundation for Lineage-Based Distributed Computation

Philipp Haller, Heather Christine Klug

The most successful systems for "big data'' processing have all adopted functional APIs. We present a new programming model we call function passing designed to provide a more principled substrate, or middleware, upon which to build data-centric distribute ...

Cambridge University Press2018

Learning-Based Hardware Design for Data Acquisition Systems

Cosimo Aprile

This multidisciplinary research work aims to investigate the optimized information extraction from signals or data volumes and to develop tailored hardware implementations that trade-off the complexity of data acquisition with that of data processing, conc ...

EPFL2018

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