activity
20102022
most citedNaNet: a flexible and configurable low-latency NIC for real-time trigger systems based on GPUs

24 citations · 71 across the 14 of their papers we have counts for

collaborators
Showing 2013Show all

9 papers · 1 filter

physics.ins-det2013

Applications of Many-Core Technologies to On-line Event Reconstruction in High Energy Physics Experiments

A. Gianelle, S. Amerio, D. Bastieri +10

Interest in many-core architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of many-…

physics.ins-det2013★ 6 cited

NaNet:a low-latency NIC enabling GPU-based, real-time low level trigger systems

Roberto Ammendola, Andrea Biagioni, Riccardo Fantechi +13

We implemented the NaNet FPGA-based PCI2 Gen2 GbE/APElink NIC, featuring GPUDirect RDMA capabilities and UDP protocol management offloading. NaNet is able to receive a UDP input da…

cs.AR2013

Architectural improvements and 28 nm FPGA implementation of the APEnet+ 3D Torus network for hybrid HPC systems

Roberto Ammendola, Andrea Biagioni, Ottorino Frezza +7

Modern Graphics Processing Units (GPUs) are now considered accelerators for general purpose computation. A tight interaction between the GPU and the interconnection network is the…

physics.ins-det2013★ 4 cited

Many-core applications to online track reconstruction in HEP experiments

S. Amerio, D. Bastieri, M. Corvo +10

Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphi…

physics.ins-det2013★ 24 cited

NaNet: a flexible and configurable low-latency NIC for real-time trigger systems based on GPUs

R. Ammendola, A. Biagioni, O. Frezza +10

NaNet is an FPGA-based PCIe X8 Gen2 NIC supporting 1/10 GbE links and the custom 34 Gbps APElink channel. The design has GPUDirect RDMA capabilities and features a network stack pr…

cs.DC2013★ 8 cited

Distributed simulation of polychronous and plastic spiking neural networks: strong and weak scaling of a representative mini-application benchmark executed on a small-scale commodity cluster

Pier Stanislao Paolucci, Roberto Ammendola, Andrea Biagioni +7

We introduce a natively distributed mini-application benchmark representative of plastic spiking neural network simulators. It can be used to measure performances of existing compu…