Name
Abstract | ||
|---|---|---|
In this work, we present the use of a new high-level synthesis engine capable of generating resource-shared compute accelerators, even from very complex double-precision codes, for cell biology simulations. From the domain-specific CellML description, the compilation pipeline is able to generate hardware that is shown to achieve a performance similar to or exceeding current generation desktop CPUs, and has energy savings of up to 96% even for a single accelerator, which requires just 25–30% area on a mid-sized FPGA. |
Year | Venue | Field |
|---|---|---|
2018 | ARC | CellML,Floating point,Computer science,Parallel computing,High-level synthesis,Field-programmable gate array |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
16 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Björn Liebig | 1 | 27 | 3.38 |
| Julian Oppermann | 2 | 30 | 6.88 |
| Oliver Sinnen | 3 | 382 | 38.71 |
| Andreas Koch | 4 | 94 | 15.13 |