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

An out-of-core stencil computation code handles large data whose size is beyond the capacity of GPU memory. Whereas, such an code requires streaming data to and from the GPU frequently. As a result, data movement between the CPU and GPU…

The ALICE High-Level Trigger processes data online, to either select interesting (sub-) events, or to compress data efficiently by modeling techniques. Focusing on the main data source, the Time Projection Chamber, the architecure of the…

During the upcoming Run 3 and Run 4 at the LHC the upgraded ALICE (A Large Ion Collider Experiment) will operate at a significantly higher luminosity and will collect two orders of magnitude more events than in Run 1 and Run 2. A part of…

Deploying large language models (LLMs) for online inference is often constrained by limited GPU memory, particularly due to the growing KV cache during auto-regressive decoding. Hybrid GPU-CPU execution has emerged as a promising solution…

The ALICE experiment is equipped with a wide range of detectors providing excellent tracking and particle identification in the central region, as well as forward detectors with extended pseudorapidity coverage, which are well suited for…

The ALICE Experiment at the Large Hadron Collider (LHC) underwent a major upgrade during the Long Shutdown 2. Several subsystems have been improved, including the ALICE Inner Tracking System (ITS), which has been entirely replaced. The new…

Generative model based image lossless compression algorithms have seen a great success in improving compression ratio. However, the throughput for most of them is less than 1 MB/s even with the most advanced AI accelerated chips, preventing…

Approximately 18 percent of the 3.2 million smartphone applications rely on integrated graphics processing units (GPUs) to achieve competitive performance. Graphics performance, typically measured in frames per second, is a strong function…

Cardinality estimation is a cornerstone of cost-based optimizers (CBOs), yet real-world workloads often violate the assumptions behind static statistics, degrading decision stability and increasing plan flip rates. We empirically…

We overview recent jet measurements in pp and Pb-Pb collisions with the ALICE detector. ALICE reconstructs jets at midrapidity using the anti-$k_{\mathrm{T}}$ algorithm, including both charged particle jets from the ALICE tracking…

ALICE (A Large Ion Collider Experiment) at the CERN Large Hadron Collider (LHC) is designed to study p-p and Pb-Pb collisions at ultra-relativistic energies. ALICE is equipped with a Muon Spectrometer (MS) to study the heavy charmonia in…

The latest generation of Timepix series hybrid pixel detectors enhance particle tracking with high spatial and temporal resolution. However, their high hit-rate capability poses challenges for data processing, particularly in multidetector…

Purpose: Image reconstruction in challenging scenarios requires accurate characterisations of coil sensitivity profiles, local off-resonances (B0) and effective encoding fields. Reconstruction methods utilising all of this information rely…

Image segmentation plays an important role in computer vision, object detection, traffic control, and video surveillance. Typically, it is a critical step in the 3D reconstruction of a specific organ in medical image processing which…

For Open IoT, we have proposed Tacit Computing technology to discover the devices that have data users need on demand and use them dynamically and an automatic GPU offloading technology as an elementary technology of Tacit Computing.…

In Run-3, beginning in 2022, the LHCb software trigger will start reconstructing events at the LHC average crossing rate of 30 MHz. Within the upgraded DAQ system, LHCb established a testbed for new heterogeneous computing solutions for…

Ultra-reliable low-latency vehicular communications (URLLC) require sufficient physical-layer (PHY) compute headroom at the network edge, where roadside units (RSUs) and compact next-generation base stations (gNBs) must meet strict timing…

The ALICE ITS3 project foresees the use of ultra-light MAPS, developed in the 65 nm imaging process, for the vertex detector in the ALICE experiment at the LHC to drastically improve the vertexing performance. This new development,…

Graphics processing units (GPUs) can improve deep neural network inference throughput via batch processing, where multiple tasks are concurrently processed. We focus on novel scenarios that the energy-constrained mobile devices offload…

GPU decoding significantly accelerates the output of ASR predictions. While GPUs are already being used for online ASR decoding, post-processing and rescoring on GPUs have not been properly investigated yet. Rescoring with available…