# Accelerating Data: Lossless Compression for HPC, Datacenter, AI, and Scientific Data Pipelines

- Institution: CERN
- Speaker: Calliope-Louisa Sotiropoulou
- Year: 2026
- Language: English
- Source: [CERN](https://videos.cern.ch/record/3025777)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

High-performance computing and data-intensive infrastructures are increasingly limited by data movement rather than processing power. Large scientific experiments such as those at CERN, together with AI training clusters and datacenters, generate continuous data streams that must be handled at multi-100 Gb/s under strict latency, power, and storage constraints. Lossless compression in FPGA or ASIC hardware reduces bandwidth and memory needs without altering scientific results, precision, or training accuracy. This presentation examines hardware architectures for lossless compression in HPC, AI, datacenter, and scientific data acquisition systems. Emphasis is on deterministic-latency pipelines operating inline with Ethernet, PCIe, high-bandwidth memory, and storage. Algorithms including LZ4, Snappy, GZIP/DEFLATE/Zlib, and Zstandard are compared in terms of ratio, resource cost, and throughput, highlighting the trade-off between ultra-low-latency cores and higher-ratio formats.

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## Lectures

1. [Accelerating Data: Lossless Compression for HPC, Datacenter, AI, and Scientific Data Pipelines](https://invisiblenetwork.ai/learn/cern/3025777/c157589dbb8d), 28 min (CERN's player)