Mario Paulo Drumond Lages De Oliveira

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The wide adoption of DNNs has given birth to unrelenting computing requirements, forcing datacenter operators to adopt domain-specific accelerators to train them. These accelerators typically employ densely packed full-precision floating-point arithmetic t ...

DNN inference accelerators executing online services exhibit low average loads because of service demand variability, leading to poor resource utilization. Unfortunately, reclaiming idle inference cycles is difficult as other workloads can not execute on a ...

Deep neural network (DNN) inference tasks are computationally expensive. Digital DNN accelerators offer better density and energy efficiency than general-purpose processors but still not sufficient to be deployable on resource-constrained settings.Analog c ...

Deep neural network inference accelerators are deployed at scale to accommodate online services, but face low average load because of service demand variability, leading to poor resource utilization. Unfortunately, reclaiming inference idle cycles is diffi ...

The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling. As the performance density of traditional CPU-centric architectures stagnates, adva ...

Data transformer apparatus comprising at least a dispatcher module (D), a reader module (R), a converter module (C) and a writer module (W). The dispatcher module (D) is configured to: receive a data transformation request (DTR) including: a first informat ...

Modern online services are shifting away from monolithic applications to loosely-coupled microservices because of their improved scalability, reliability, programmability and development velocity. Microservices communicating over the datacenter network req ...

Mario Paulo Drumond Lages De Oliveira

Chattez avec Graph Search

Training DNNs with Hybrid Block Floating Point

Equinox: Training (for Free) on a Custom Inference Accelerator

Analog Neural Networks with Deep-submicron Nonlinear Synapses

ColTraIn: Co-located DNN training and inference

The Mondrian Data Engine

Data transformer apparatus

Optimus Prime: Accelerating Data Transformation in Servers