Publications by Alexandros Daglis

Cooperative Concurrency Control for Write-Intensive Key-Value Workloads

Babak Falsafi, Alexandros Daglis, Mark Johnathon Sutherland

Key-Value Stores (KVS) are foundational infrastructure components for online services. Due to their latency-critical nature, today’s best-performing KVS contain a plethora of full-stack optimizations commonly targeting read-mostly, popularity-skewed worklo ...

ACM2023

Cerebros: Evading the RPC Tax in Datacenters

Babak Falsafi, Alexandros Daglis, Arash Pourhabibi Zarandi, Mark Johnathon Sutherland

The emerging paradigm of microservices decomposes online services into fine-grained software modules frequently communicating over the datacenter network, often using Remote Procedure Calls (RPCs). Ongoing advancements in the network stack have exposed the ...

2021

The NEBULA RPC-Optimized Architecture

Babak Falsafi, Alexandros Daglis, Mark Johnathon Sutherland, Dionysios Pnevmatikatos, Siddharth Gupta

Large-scale online services are commonly structured as a network of software tiers, which communicate over the datacenter network using RPCs. Ongoing trends towards software decomposition have led to the prevalence of tiers receiving and generating RPCs wi ...

2020

Exploiting Errors for Efficiency: A Survey from Circuits to Applications

Damien Zufferey, Babak Falsafi, Sasa Misailovic, Eva Darulova, Dorde Jevdic, Alexandros Daglis, Mattia Cacciotti

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from cor ...

ASSOC COMPUTING MACHINERY2020

RPCValet: NI-Driven Tail-Aware Balancing of µs-Scale RPCs

Babak Falsafi, Alexandros Daglis, Mark Johnathon Sutherland

Modern online services come with stringent quality requirements in terms of response time tail latency. Because of their decomposition into fine-grained communicating software layers, a single user request fans out into a plethora of short, μs-scale RPCs, ...

ACM2019

Mitigating Load Imbalance in Distributed Data Serving with Rack-Scale Memory Pooling

Babak Falsafi, Stanko Novakovic, Boris Robert Grot, Alexandros Daglis, Edouard Bugnion, Dmitrii Ustiugov

To provide low-latency and high-throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution of k ...

2019

Distributed Logless Atomic Durability with Persistent Memory

Babak Falsafi, Alexandros Daglis, Siddharth Gupta

Datacenter operators have started deploying Persistent Memory (PM), leveraging its combination of fast access and persistence for significant performance gains. A key challenge for PM-aware software is to maintain high performance while achieving atomic du ...

2019

Atomic object reads for in-memory rack-scale computing

Babak Falsafi, Boris Robert Grot, Alexandros Daglis

A distributed memory system including a plurality of chips, a plurality of nodes that are distributed across the plurality of chips such that each node is comprised within a chip, each node includes a dedicated local memory and a processor core, and each l ...

2018

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

Alexandros Daglis

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 ...

EPFL2018

Design Guidelines for High-Performance SCM Hierarchies

Babak Falsafi, Javier Picorel Obando, Alexandros Daglis, Edouard Bugnion, Dmitrii Ustiugov, Mark Johnathon Sutherland, Dionysios Pnevmatikatos

With emerging storage-class memory (SCM) nearing commercialization, there is evidence that it will deliver the much-anticipated high density and access latencies within only a fewfactors of DRAM. Nevertheless, the latency-sensitive nature of memory-residen ...

ACM2018

The Mondrian Data Engine

Babak Falsafi, Javier Picorel Obando, Boris Robert Grot, Alexandros Daglis, Nooshin Sadat Mirzadeh, Dmitrii Ustiugov, Mario Paulo Drumond Lages De Oliveira, Dionysios Pnevmatikatos

The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling. As the performance density of traditional CPU-centric architectures stagnates, adva ...

2017

The Case for RackOut: Scalable Data Serving Using Rack-Scale Systems

Babak Falsafi, Stanko Novakovic, Boris Robert Grot, Alexandros Daglis, Edouard Bugnion

To provide low latency and high throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution of k ...

2016

An Analysis of Load Imbalance in Scale-out Data Serving

Babak Falsafi, Stanko Novakovic, Boris Robert Grot, Alexandros Daglis, Edouard Bugnion

Despite the natural parallelism across lookups, performance of distributed key-value stores is often limited due to load imbalance induced by heavy skew in the popularity distribution of the dataset. To avoid violating service level objectives expressed in ...

2016

SABRes: Atomic Object Reads for In-Memory Rack-Scale Computing

Babak Falsafi, Stanko Novakovic, Boris Robert Grot, Alexandros Daglis, Edouard Bugnion, Dmitrii Ustiugov

Modern in-memory services rely on large distributed object stores to achieve the high scalability essential to service thousands of requests concurrently. The independent and unpredictable nature of incoming requests results in random accesses to the objec ...

Ieee2016

Scale-out non-uniform memory access

Babak Falsafi, Stanko Novakovic, Boris Robert Grot, Alexandros Daglis, Edouard Bugnion

A computing system that uses a Scale-Out NUMA (“soNUMA”) architecture, programming model, and/or communication protocol provides for low-latency, distributed in-memory processing. Using soNUMA, a programming model is layered directly on top of a NUMA memor ...

2015

Manycore Network Interfaces for In-Memory Rack-Scale Computing

Babak Falsafi, Stanko Novakovic, Boris Robert Grot, Alexandros Daglis, Edouard Bugnion

Datacenter operators rely on low-cost, high-density technologies to maximize throughput for data-intensive services with tight tail latencies. In-memory rack-scale computing is emerging as a promising paradigm in scale-out datacenters capitalizing on commo ...

2015

Scale-Out NUMA

Babak Falsafi, Stanko Novakovic, Boris Robert Grot, Alexandros Daglis, Edouard Bugnion

Emerging datacenter applications operate on vast datasets that are kept in DRAM to minimize latency. The large number of servers needed to accommodate this massive memory footprint requires frequent server-to-server communication in applications such as ke ...

2014