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Error-bounded lossy compression is a critical technique for significantlyreducing scientific data volumes. Compared to CPU-based compressors, GPU-basedcompressors exhibit substantially higher throughputs, fitting better fortoday's HPC applications. However, the critical limitations of existingGPU-based compressors are their low compression ratios and qualities, severelyrestricting their applicability. To overcome these, we introduce a newGPU-based error-bounded scientific lossy compressor named cuSZ-$i$, with thefollowing contributions: (1) A novel GPU-optimized interpolation-basedprediction method significantly improves the compression ratio anddecompression data quality. (2) The Huffman encoding module in cuSZ-$i$ isoptimized for better efficiency. (3) cuSZ-$i$ is the first to integrate theNVIDIA Bitcomp-lossless as an additional compression-ratio-enhancing module.Evaluations show that cuSZ-$i$ significantly outperforms other latest GPU-basedlossy compressors in compression ratio under the same error bound (hence, thedesired quality), showcasing a 476% advantage over the second-best. This leadsto cuSZ-$i$'s optimized performance in several real-world use cases.

cuSZ-$i$: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation