The minSSIM metric and SBLC, the first SSIM-bounded compressor, are introduced, which is fully CPU-GPU compatible and guarantees the user-provided minSSIM bound, which it enforces by strategically tightening the error bound on specific values in the data.
FaCTz is presented, the first GPU-based error-bounded lossy compressor that guarantees critical-point preservation and provides a block-wise mode optimized for throughput and a speculative per-point mode optimized for compression ratio.
Mingze Xia, Yu-Xiao Li, Sheng Di et al.· 0 citations
Cortado is compared with state-of-the-art approaches and it is found that it is the only progressive compressor that guarantees the evaluated error bounds on all tested inputs while achieving the highest throughputs, comparable reconstruction quality, and on-par compression ratios.
BlockMGARD is proposed, an adaptive, Region-of-Interest (ROI)-supported GPU lossy compressor, with four contributions: an In-cache Block decomposition leveraging GPU on-chip memory and constant lookup tables to accelerate decomposition; a hybrid hierarchy combining In-cache Block and global decomposition to balance spe...
Yan-Liang Li, Qian Gong, Qing Liu et al.· 0 citations
HPC (High Performance Computing) applications such as numerical simulations are memory-intensive. As memory grows scarce compared to compute power, compression could alleviate hardware demands by reducing memory footprint at runtime, especially on GPU. Existing compression algorithms for scientific data are not specifi...
T. Hovi, François Letierce, L. Lucas· Proceedings of the Internati...· 0 citations
Random access into compressed data is normally bought with density. We measure the exchange rate. Across four formats and nine axes on a common corpus, the cost of cutting a 254 MB archive into independently addressable 16 KiB units is 1.632% of the archive for an absolute-offset format against 6.57% for seekable zstd,...
NVFP4 is an attractive datatype for large language model (LLM) inference, offering compact storage and native tensor-core acceleration. However, preserving accuracy using NVFP4 requires careful quantization. In this work we develop a novel quantization scheme called Optimized Smoothing and Scaling for NVFP4 (OSFP4). Fo...
N. B. Ben-David, Or Meir, Or Ordentlich· 0 citations
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