National audiencePredicting the performance of Artificial NeuralNetworks (ANNs) on embedded multi-core platforms is tedious.Concurrent accesses to shared resources are hard to model dueto congestion effects on the shared communication medium,which affect the performance of the application. In this paperwe present a hybrid modeling environment to enable fast yetaccurate timing prediction for fully-connected ANNs deployedon multi-core platforms. The modeling flow is based on theintegration of an analytical computation time model with acommunication time model which are both calibrated throughmeasurement inside a system level simulation using SystemC. Theproposed flow enables the prediction of the end-to-end latencyfor different mappings of se...
The final publication is available at ACM via http://dx.doi.org/10.1145/3229607.3229613Recent trends...
Network latency is a crucial factor affecting the quality of communications networks due to the irre...
International audienceFast yet accurate performance and timing prediction of complex parallel data f...
National audiencePredicting the performance of Artificial NeuralNetworks (ANNs) on embedded multi-co...
Predicting the performance of Artificial Neural Networks (ANNs) on embedded multi-core platforms is ...
International audiencePredicting the performance of Artificial Neural Networks(ANNs) on embedded mul...
Evaluation of performance for complex applications such as Artificial Intelligence (AI) algorithms a...
International audienceWhen deploying Artificial Neural Networks (ANNs) onto multi-core embedded plat...
National audienceEvaluation of performance for complex applicationssuch as Artificial Intelligence (...
Early evaluation of Neural Networks (NN) deployments on multi-core platforms is necessary to find de...
Abstract. We present an estimation methodology, accurately predicting the execution time for a given...
. A performance prediction method is presented for indicating the performance range of MIMD parallel...
Assisted partial timing support is a method to enhance the synchronization of communication networks...
Deep neural networks have revolutionized multiple fields within computer science. It is important to...
International audienceFast yet accurate performance and timing prediction of complexparallel data fl...
The final publication is available at ACM via http://dx.doi.org/10.1145/3229607.3229613Recent trends...
Network latency is a crucial factor affecting the quality of communications networks due to the irre...
International audienceFast yet accurate performance and timing prediction of complex parallel data f...
National audiencePredicting the performance of Artificial NeuralNetworks (ANNs) on embedded multi-co...
Predicting the performance of Artificial Neural Networks (ANNs) on embedded multi-core platforms is ...
International audiencePredicting the performance of Artificial Neural Networks(ANNs) on embedded mul...
Evaluation of performance for complex applications such as Artificial Intelligence (AI) algorithms a...
International audienceWhen deploying Artificial Neural Networks (ANNs) onto multi-core embedded plat...
National audienceEvaluation of performance for complex applicationssuch as Artificial Intelligence (...
Early evaluation of Neural Networks (NN) deployments on multi-core platforms is necessary to find de...
Abstract. We present an estimation methodology, accurately predicting the execution time for a given...
. A performance prediction method is presented for indicating the performance range of MIMD parallel...
Assisted partial timing support is a method to enhance the synchronization of communication networks...
Deep neural networks have revolutionized multiple fields within computer science. It is important to...
International audienceFast yet accurate performance and timing prediction of complexparallel data fl...
The final publication is available at ACM via http://dx.doi.org/10.1145/3229607.3229613Recent trends...
Network latency is a crucial factor affecting the quality of communications networks due to the irre...
International audienceFast yet accurate performance and timing prediction of complex parallel data f...