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On the Performance of Delegation over Cache-Coherent Shared Memory

Publications associées (34)

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Rebooting Virtual Memory with Midgard

Siddharth Gupta

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

EPFL2023

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Ali Pahlevan

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

2022

How Many CPU Cores is an FPGA Worth? Lessons Learned from Accelerating String Sorting on a CPU-FPGA System

Paolo Ienne, Mikhail Asiatici, Damian Maiorano

String sorting is a fundamental kernel of string matching and database index construction; yet, it has not been studied as extensively as fixed-length keys sorting. Because processing variable-length keys in hardware is challenging, it is no surprise that ...

SPRINGER2021

FPGAs in the Datacenters: the Case of Parallel Hybrid Super Scalar String Sample Sort

Paolo Ienne, Mikhail Asiatici, Damian Maiorano

String sorting is an important part of database and MapReduce applications; however, it has not been studied as extensively as sorting of fixed-length keys. Handling variable-length keys in hardware is challenging and it is no surprise that no string sorte ...

IEEE COMPUTER SOC2020

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Virtual memory (VM) is critical to the usability and programmability of hardware accelerators. Unfortunately, implementing accelerator VM efficiently is challenging because the area and power constraints make it difficult to employ the large multi-level TL ...

2020

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Modern server hardware is increasingly heterogeneous as hardware accelerators, such as GPUs, are used together with multicore CPUs to meet the computational demands of modern data analytics workloads. Unfortunately, query parallelization techniques used by ...

2019

CoreNEURON : An Optimized Compute Engine for the NEURON Simulator

Felix Schürmann, James Gonzalo King, Michael Lee Hines, Pramod Shivaji Kumbhar, Aleksandr Ovcharenko, Jérémy Pierre Benoit Fouriaux

The NEURON simulator has been developed over the past three decades and is widely used by neuroscientists to model the electrical activity of neuronal networks. Large network simulation projects using NEURON have supercomputer allocations that individually ...

2019

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

An Analytical Model of Hardware Transactional Memory

Willy Zwaenepoel, Paolo Romano, Diego Didona

This paper investigates the problem of deriving a white box performance model of Hardware Transactional Memory (HTM) systems. The proposed model targets TSX, a popular implementation of HTM integrated in Intel processors starting with the Haswell family in ...

2017

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Modern hardware is abundantly parallel and increasingly heterogeneous. The numerous processing cores have non-uniform access latencies to the main memory and processor caches, which causes variability in the communication costs. Unfortunately, database sys ...

Springer Verlag2016