Oracular Byzantine Reliable Broadcast

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In the problem of private information retrieval with side information, a single user wants to recover one of the K independent messages which are stored at one or multiple servers. The user initially has a subset of messages as side information. The goal o ...

This paper addresses the mean-field behavior of large-scale systems of parallel servers with a processor sharing service discipline when arrivals are Poisson and jobs have general service time distributions when an SQ(d) routing policy is used. Under this ...

In online data-intensive (OLDI) services, each client request typically executes on multiple servers in parallel; as a result, “system hiccups”, although rare within a single server, can interfere with many client requests and cause violations of service-l ...

Computer systems designers are building cache hierarchies with higher capacity to capture the ever-increasing working sets of modern workloads. Cache hierarchies with higher capacity improve system performance but shift the performance bottleneck to addres ...

The booming popularity of online services is rapidly raising the demands for modern datacenters. In order to cope with data deluge, growing user bases, and tight quality of service constraints, service providers deploy massive datacenters with tens to hund ...

Causal consistency is an attractive consistency model for geo-replicated data stores. It is provably the strongest model that tolerates network partitions. It avoids the long latencies associated with strong consistency, and, especially when using read-onl ...

We present GARFIELD, a library to transparently make machine learning (ML) applications, initially built with popular (but fragile) frameworks, e.g., TensorFlow and PyTorch, Byzantine–resilient. GARFIELD relies on a novel object–oriented design, reducing t ...

In distributed optimization, parameter updates from the gradient computing node devices have to be aggregated in every iteration on the orchestrating server. When these updates are sent over an arbitrary commodity network, bandwidth and latency can be limi ...

Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automati ...

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 ...

Huge scale machine learning problems are nowadays tackled by distributed optimization algorithms, i.e. algorithms that leverage the compute power of many devices for training. The communication overhead is a key bottleneck that hinders perfect scalability. ...

The single-server multi-message private information retrieval with side information problem is studied for general cases. In this problem, K independent messages are stored at a single server. One user initially has M messages as side information and wants ...

Caching is a technique that alleviates networks during peak hours by transmitting partial information before a request for any is made. In a lossy setting of Gaussian databases, we study a single-user model in which good caching strategies minimize the dat ...

Cloud Computing aims to efficiently tackle the increasing demand of computing resources, and its popularity has led to a dramatic increase in the number of computing servers and data centers worldwide. However, as effect of post-Dennard scaling, computing ...

Oracular Byzantine Reliable Broadcast

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Single-server Multi-user Private Information Retrieval with Side Information

The mean-field behavior of processor sharing systems with general job lengths under the SQ(d) policy

When to Hedge in Interactive Services

Rebooting Virtual Memory with Midgard

Network-Compute Co-Design for Distributed In-Memory Computing

Causal Consistency and Latency Optimality: Friend or Foe? [Extended Version]

GARFIELD: System Support for Byzantine Machine Learning (Regular Paper)

Causal Consistency and Latency Optimality: Friend or Foe?

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

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

Sparsified SGD with Memory

Single-server Multi-message Private Information Retrieval with Side Information: the General Cases

Caching (Bivariate) Gaussians

Energy Proportionality in Near-Threshold Computing Servers and Cloud Data Centers: Consolidating or Not?