Name
Abstract | ||
|---|---|---|
Exchanging large amounts of floating-point data is common in distributed scientific computing applications. Data compression, when fast enough, can speed up such workloads by reducing the time spent waiting for data transfers. We propose ndzip, a high-throughput, lossless compression algorithm for multi-dimensional univariate regular grids of single- and double-precision floating point data. Tailo... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/DCC50243.2021.00018 | 2021 Data Compression Conference (DCC) |
Keywords | DocType | ISSN |
Program processors,Scientific computing,Multicore processing,Memory management,Data compression,Distributed databases,Bandwidth | Conference | 1068-0314 |
ISBN | Citations | PageRank |
978-1-6654-0333-7 | 2 | 0.41 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabian Knorr | 1 | 2 | 0.41 |
| Peter Thoman | 2 | 79 | 13.20 |
| Thomas Fahringer | 3 | 2847 | 254.09 |