Achieves significant storage savings without the "CPU tax" usually associated with heavy compression.
The study addresses the in supercomputing. As CPUs get faster, moving data to storage (Parallel File Systems like Lustre or GPFS) remains slow. This research proposes a high-throughput compression framework designed to: Reduce the physical footprint of scientific data. Minimize the time spent on disk I/O operations.
Optimization parameters for Lustre and Spectrum Scale file systems. 📈 Performance Impact sc23050-HPDC.rar
The file refers to the experimental datasets and artifacts for the research paper titled "SC23050: High-Performance Data Compression on Parallel File Systems."
📍 The framework demonstrates an I/O throughput increase of 2x to 5x compared to uncompressed writes. Achieves significant storage savings without the "CPU tax"
Maintain high performance across thousands of parallel compute nodes. 🛠️ Technical Breakdown 1. The HPDC Framework
Dynamically splits scientific datasets based on data entropy (randomness) to choose the best compression ratio. 📈 Performance Impact The file refers to the
Overlaps the compression of "Chunk B" while "Chunk A" is still being written to the file system. 3. RAR Archive Contents The sc23050-HPDC.rar package typically contains: