Related papers: ROOT I/O compression algorithms and their performa…
Upcoming HEP experiments, e.g. at the HL-LHC, are expected to increase the volume of generated data by at least one order of magnitude. In order to retain the ability to analyze the influx of data, full exploitation of modern storage…
The ROOT TTree data format encodes hundreds of petabytes of High Energy and Nuclear Physics events. Its columnar layout drives rapid analyses, as only those parts ("branches") that are really used in a given analysis need to be read from…
The upgrade to the ATLAS trigger for LHC Run 2 is presented including a description of the design and performance of the newly reimplemented tracking algorithms. The profiling infrastructure, constructed to provide prompt feedback from the…
Modern scientific simulations generate massive volumes of data, creating significant challenges for I/O and storage systems. Error-bounded lossy compression (EBLC) offers a solution by reducing data set sizes while preserving data quality…
Recent advancements in large language models (LLMs) have enabled their successful application to a broad range of tasks. However, in information-intensive tasks, the prompt length can grow fast, leading to increased computational…
The rapid growth of digital data has heightened the demand for efficient lossless compression methods. However, existing algorithms exhibit trade-offs: some achieve high compression ratios, others excel in encoding or decoding speed, and…
Starting in 2022, the upgraded LHCb detector will collect data with a pure software trigger. In its first stage, reducing the rate from 30MHz to about 1MHz, GPUs are used to reconstruct and trigger on B and D meson topologies and high-pT…
In data storage and transmission, file compression is a common technique for reducing the volume of data, reducing data storage space and transmission time and bandwidth. However, there are significant differences in the compression…
The LHCb collaboration continues to heavily utilize the Run 1 and Run 2 legacy datasets well into Run 3. As the operational focus shifts from the legacy data to the live Run 3 samples, it is vital that a sustainable and efficient system is…
The escalating surge in data generation presents formidable challenges to information technology, necessitating advancements in storage, retrieval, and utilization. With the proliferation of artificial intelligence and big data, the "Data…
In LHC Run 3, ALICE will increase the data taking rate significantly, from an approximately 1 kHz trigger readout in minimum-bias Pb--Pb collisions to a 50 kHz continuous readout rate. The reconstruction strategy of the online-offline…
Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) architecture, GPU-accelerated error-bounded compressors (such as…
Because of the vast volume of data being produced by today's scientific simulations, lossy compression allowing user-controlled information loss can significantly reduce the data size and the I/O burden. However, for large-scale cosmology…
Robust optimization over time (ROOT) refers to an optimization problem where its performance is evaluated over a period of future time. Most of the existing algorithms use particle swarm optimization combined with another method which…
In LHC Run 3, ALICE will increase the data taking rate significantly to 50 kHz continuous read out of minimum bias Pb-Pb collisions. The reconstruction strategy of the online offline computing upgrade foresees a first synchronous online…
In the recent years, heterogeneous machine learning accelerators have become of significant interest in science, engineering and industry. The major processing speed bottlenecks in these platforms come from (a) an electronic data…
Large language models (LLMs) excel at language understanding and generation, but their enormous computational and memory requirements hinder deployment. Compression offers a potential solution to mitigate these constraints. However, most…
LLM-powered agents often use prompt compression to reduce inference costs, but this introduces a new security risk. Compression modules, which are optimized for efficiency rather than safety, can be manipulated by adversarial inputs,…
Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Data compression offers an attractive approach to reducing communication costs by using available bandwidth effectively.…
Software caches are an intrinsic component of almost every computer system. Consequently, caching algorithms, particularly eviction policies, are the topic of many papers. Almost all these prior papers evaluate the caching algorithm based…