56 citations · 60 across the 4 of their papers we have counts for
6 papers
No-Restart Elasticity in an Adaptive Runtime System for Cloud-Native HPC
Aditya Bhosale, Laxmikant Kale
Exploiting discounted spot instances for HPC requires an application to change its resource allocation at runtime, shrinking ahead of an interruption and expanding onto replacement…
Efficient and Portable Support for Overdecomposition on Distributed Memory GPGPU Platforms
Aditya Bhosale, Anant Jain, Shourya Goel +3
Overdecomposition has emerged as a powerful and sometimes essential technique in parallel programming. Many application domains or frameworks, including those based on adaptive mes…
Towards an Adaptive Runtime System for Cloud-Native HPC
Aditya Bhosale, Advait Tahilyani, Laxmikant Kale +1
The ongoing convergence of HPC and cloud computing presents a fundamental challenge: HPC applications, designed for static and homogeneous supercomputers, are ill-suited for the dy…
An Adaptive Distributed Stencil Abstraction for GPUs
Aditya Bhosale, Laxmikant Kale
The scientific computing ecosystem in Python is largely confined to single-node parallelism, creating a gap between high-level prototyping in NumPy and high-performance execution o…
An Elastic Job Scheduler for HPC Applications on the Cloud
Aditya Bhosale, Kavitha Chandrasekar, Laxmikant Kale +1
The last few years have seen an increase in adoption of the cloud for running HPC applications. The pay-as-you-go cost model of these cloud resources has necessitated the developme…
PySPH: a Python-based framework for smoothed particle hydrodynamics
Prabhu Ramachandran, Aditya Bhosale, Kunal Puri +17
PySPH is an open-source, Python-based, framework for particle methods in general and Smoothed Particle Hydrodynamics (SPH) in particular. PySPH allows a user to define a complete S…