3 citations · 3 across the 4 of their papers we have counts for
5 papers
MinatoLoader: Accelerating Machine Learning Training Through Efficient Data Preprocessing
Rahma Nouaji, Stella Bitchebe, Ricardo Macedo +1
Data loaders are used by Machine Learning (ML) frameworks like PyTorch and TensorFlow to apply transformations to data before feeding it into the accelerator. This operation is cal…
MaLV-OS: Rethinking the Operating System Architecture for Machine Learning in Virtualized Clouds
Stella Bitchebe, Oana Balmau
A large body of research has employed Machine Learning (ML) models to develop learned operating systems (OSes) and kernels. The latter dynamically adapts to the job load and dynami…
Virtual Disk Snapshot Management at Scale
Kevin Nguetchouang, Theophile Dubuc, Stella Bitchebe +2
Contrary to the other resources such as CPU, memory, and network, for which virtualization is efficiently achieved through direct access, disk virtualization is peculiar. In this p…
Out of Hypervisor (OoH): When Nested Virtualization Becomes Practical
Stella Bitchebe, Alain Tchana
This paper introduces Out of Hypervisor (OoH), a new research axis close to nested virtualization. Instead of emulating a full virtual hardware inside a VM to support a hypervisor,…
Intel Page Modification Logging, a hardware virtualization feature: study and improvement for virtual machine working set estimation
Stella Bitchebe, Djob Mvondo, Alain Tchana +2
Intel Page Modification Logging (PML) is a novel hardware feature for tracking virtual machine (VM) accessed memory pages. This task is essential in today's data centers since it a…