54 citations · 69 across the 6 of their papers we have counts for
13 papers
Higgs Boson Classification: Brain-inspired BCPNN Learning with StreamBrain
Martin Svedin, Artur Podobas, Steven W. D. Chien +1
One of the most promising approaches for data analysis and exploration of large data sets is Machine Learning techniques that are inspired by brain models. Such methods use alterna…
Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers
Martin Svedin, Steven W. D. Chien, Gibson Chikafa +2
For many, Graphics Processing Units (GPUs) provides a source of reliable computing power. Recently, Nvidia introduced its 9th generation HPC-grade GPUs, the Ampere 100, claiming si…
StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs
Artur Podobas, Martin Svedin, Steven W. D. Chien +5
The modern deep learning method based on backpropagation has surged in popularity and has been used in multiple domains and application areas. At the same time, there are other --…
Performance Evaluation of Advanced Features in CUDA Unified Memory
Steven W. D. Chien, Ivy B. Peng, Stefano Markidis
CUDA Unified Memory improves the GPU programmability and also enables GPU memory oversubscription. Recently, two advanced memory features, memory advises and asynchronous prefetch,…
Posit NPB: Assessing the Precision Improvement in HPC Scientific Applications
Steven W. D. Chien, Ivy B. Peng, Stefano Markidis
Floating-point operations can significantly impact the accuracy and performance of scientific applications on large-scale parallel systems. Recently, an emerging floating-point for…
Multi-GPU Acceleration of the iPIC3D Implicit Particle-in-Cell Code
Chaitanya Prasad Sishtla, Steven W. D. Chien, Vyacheslav Olshevsky +2
iPIC3D is a widely used massively parallel Particle-in-Cell code for the simulation of space plasmas. However, its current implementation does not support execution on multiple GPU…