In this paper, we present a new network protocol and methodology to enhance the configuration phase of the SpiNNaker spiking neural network hardware simulator. We have developed a system able to accept and process on-board a set of configuration primitives (data specification) encapsulated into ad-hoc packets, avoiding the management of chip memory from the host computer. We performed a study of the data specification generator implemented in the host software library. Afterwards, we extended the currently on-board data specification executor to cope with the newly-formed packets. The use of UDP protocol presents challenges due to its intrinsic unreliability. Furthermore, the presence of a single Ethernet link per board, and the requirement...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
One of the main challenges in neuromorphic VLSI systems is the design of the communication infrastru...
In this paper we present a new Partitioning and Placement methodology able to maps Spiking Neural Ne...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
Abstract — SpiNNaker is a massively-parallel neuromorphic computing architecture designed to model v...
Abstract—This paper presents the algorithm and software developed for parallel simulation of spiking...
Abstract—This paper presents the algorithm and software developed for parallel simulation of spiking...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
This work presents sPyNNaker 4.0.0, the latest version of the software package for simulating PyNN-d...
Abstract—With neuromorphic hardware rapidly moving towards large-scale, possibly immovable systems c...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
One of the main challenges in neuromorphic VLSI systems is the design of the communication infrastru...
In this paper we present a new Partitioning and Placement methodology able to maps Spiking Neural Ne...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
In this paper, we present a new network protocol and methodology to enhance the configuration phase ...
Abstract — SpiNNaker is a massively-parallel neuromorphic computing architecture designed to model v...
Abstract—This paper presents the algorithm and software developed for parallel simulation of spiking...
Abstract—This paper presents the algorithm and software developed for parallel simulation of spiking...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
This work presents sPyNNaker 4.0.0, the latest version of the software package for simulating PyNN-d...
Abstract—With neuromorphic hardware rapidly moving towards large-scale, possibly immovable systems c...
Neuromorphic architectures are emerging not only for real-time simulation of brain-scale biological ...
One of the main challenges in neuromorphic VLSI systems is the design of the communication infrastru...
In this paper we present a new Partitioning and Placement methodology able to maps Spiking Neural Ne...