Publications by Stanko Novakovic

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

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

Rack-Scale Memory Pooling for Datacenters

Stanko Novakovic

The rise of web-scale services has led to a staggering growth in user data on the Internet. To transform such a vast raw data into valuable information for the user and provide quality assurances, it is important to minimize access latency and enable in-me ...

EPFL2017

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

DeepDive: Transparently Identifying and Managing Performance Interference in Virtualized Environments

Ricardo Bianchini, Dejan Kostic, Nedeljko Vasic, Dejan Novakovic, Stanko Novakovic

2013