Related papers: GPU performance in Run3 ALICE online/offline recon…

The Animation-based Generative Codec (AGC) is an emerging paradigm for talking-face video compression. However, deploying its intricate decoder on resource and power-constrained edge devices presents challenges due to numerous parameters,…

We propose a GPU-accelerated distributed optimization algorithm for controlling multi-phase optimal power flow in active distribution systems with dynamically changing topologies. To handle varying network configurations and enable…

Ptychography is a popular microscopic imaging modality for many scientific discoveries and sets the record for highest image resolution. Unfortunately, the high image resolution for ptychographic reconstruction requires significant amount…

ALICE is the LHC experiment dedicated to the study of heavy-ion collisions. At forward rapidity a muon spectrometer detects muons from low mass mesons, quarkonia, open heavy-flavor hadrons as well as weak bosons. A muon selection based on…

A selection of recent ALICE results from pp, p--Pb, Pb--Pb and Xe--Xe collisions taken during the Run 1 and Run 2 phases are summarized in this contribution, and the prospects for the upcoming Run 3 phase are outlined.

Fast 3D data analysis and steering of a tomographic experiment by changing environmental conditions or acquisition parameters require fast, close to real-time, 3D reconstruction of large data volumes. Here we present a performance-optimized…

As graph analytics often involves compute-intensive operations, GPUs have been extensively used to accelerate the processing. However, in many applications such as social networks, cyber security, and fraud detection, their representative…

The ALICE experiment at the CERN Large Hadron Collider (LHC) is a multi-purpose particle detector, mainly focused on the study of quark-gluon plasma (QGP) in heavy-ion collisions. In the forward rapidity region, 2.5 $<$ y $<$ 4, ALICE is…

In GPU-accelerated data analytics, the overhead of data transfer from CPU to GPU becomes a performance bottleneck when the data scales beyond GPU memory capacity due to the limited PCIe bandwidth. Data compression has come to rescue for…

After a highly successful first data taking period at the LHC, the LHCb experiment developed a new trigger strategy with a real-time reconstruction, alignment and calibration for Run II. This strategy relies on offline-like track…

Skeleton-based Graph Convolutional Networks (GCNs) models for action recognition have achieved excellent prediction accuracy in the field. However, limited by large model and computation complexity, GCNs for action recognition like 2s-AGCN…

The ALICE experiment at the Large Hadron Collider (LHC) at CERN is optimized for recording events in the very large particle multiplicity environment of heavy-ion collisions at LHC energies. The ALICE collaboration has taken data in Pb-Pb…

Advances in GPU compute throughput and memory capacity brings significant opportunities to a wide range of workloads. However, efficiently utilizing these resources remains challenging, particularly because diverse application…

GPUs are now used for a wide range of problems within HPC. However, making efficient use of the computational power available with multiple GPUs is challenging. The main challenges in achieving good performance are memory layout, affecting…

As supercomputers grow in size and complexity, power efficiency has become a critical challenge, particularly in understanding GPU power consumption within modern HPC workloads. This work addresses this challenge by presenting a data…

A Large Ion Collider Experiment (ALICE) is one of the four big CERN experiments at the LHC. The area of interest is the study of the Quark-Gluon Plasma which is produced in heavy-ion collisions. The trajectories of particles created in…

The ALICE collaboration is preparing an upgrade of the three innermost layers of the current Inner Tracking System (ITS) during the next LHC long shutdown (LS3). The new ITS detector will use wafer-scale (up to \SI{27}{cm} in length)…

Providing fault-tolerance for long-running GPU-intensive jobs requires application-specific solutions, and often involves saving the state of complex data structures spread among many graphics libraries. This work describes a mechanism for…

Diagnosing GPU tail latency spikes in cloud and HPC infrastructure is critical for maintaining performance predictability and resource utilization, yet existing monitoring tools lack the granularity for root cause analysis in shared…

BATSRUS, our state-of-the-art extended magnetohydrodynamic code, is the most used and one of the most resource-consuming models in the Space Weather Modeling Framework. It has always been our objective to improve its efficiency and speed…