Leonardo Bautista-Gomez

Albert Njoroge Kahira, Truong Thao Nguyen, Leonardo Bautista Gomez et al.

Deep Neural Network (DNN) frameworks use distributed training to enable faster time to convergence and alleviate memory capacity limitations when training large models and/or using high dimension inputs. With the steady increase in datasets and model sizes, model/hybrid parallelism is deemed to have an important role in the future of distributed training of DNNs. We analyze the compute, communication, and memory requirements of Convolutional Neural Networks (CNNs) to understand the trade-offs between different parallelism approaches on performance and scalability. We leverage our model-driven analysis to be the basis for an oracle utility which can help in detecting the limitations and bottlenecks of different parallelism approaches at scale. We evaluate the oracle on six parallelization strategies, with four CNN models and multiple datasets (2D and 3D), on up to 1024 GPUs. The results demonstrate that the oracle has an average accuracy of about 86.74% when compared to empirical results, and as high as 97.57% for data parallelism.

Mikel Cortes-Goicoechea, Leonardo Bautista-Gomez

Achieving the equilibrium between scalability, sustainability, and security while keeping decentralization has prevailed as the target solution for decentralized blockchain applications over the last years. Several approaches have been proposed by multiple blockchain teams to achieve it, Ethereum being among them. Ethereum is on the path of a major protocol improvement called Ethereum 2.0 (Eth2), implementing Sharding and introducing the Proof-of-Stake (PoS). As the change of consensus mechanism is a delicate matter, this improvement will be achieved through different phases, the first of which is the implementation of the Beacon Chain. As Ethereum1, Eth2 relies on a decentralized peer-to-peer (p2p) network for the message distribution. Up to date, we estimate that there are around 5.000 nodes in the Eth2 main net geographically distributed. However, the topology of this one still prevails unknown. In this paper, we present the results obtained from the analysis we performed on the Eth2 p2p network. Describing the topology of the network, as possible hazards that this one implies.

Mikel Cortes-Goicoechea, Luca Franceschini, Leonardo Bautista-Gomez

Scalability is a common issue among the most used permissionless blockchains, and several approaches have been proposed accordingly. As Ethereum is set to be a solid foundation for a decentralized Internet web, the need for tackling scalability issues while preserving the security of the network is an important challenge. In order to successfully deliver effective scaling solutions, Ethereum is on the path of a major protocol improvement called Ethereum 2.0 (Eth2), which implements sharding. As the change of consensus mechanism is an extremely delicate matter, this improvement will be achieved through different phases, the first of which is the implementation of the Beacon Chain. For this, a specification has been developed and multiple groups have implemented clients to run the new protocol. In this work, we analyse the resource usage behaviour of different clients running as Eth2 nodes, comparing their performance and analysing differences. Our results show multiple network perturbations and how different clients react to it.