TY  - GEN
AB  - Persistent data structures allow large and complex data structures to be copied and manipulated inexpensively. The persistent way of representing data offers opportunities to more elegantly and more efficiently implement certain algorithms and programming patterns. Few persistent data structure libraries, however, are designed with an emphasis on speed and performance compared to their mutable cousins. We describe and present a C library for a persistent graph data structure, which uses array compression techniques and balanced wide-fanout tries to create a structure that enables persistence without sacrificing performance. Compared to a competitive C++ mutable graph library, we consistently achieve 30-40% slower random read performance using up to 30% fewer bytes in memory, with the benefit of highly space-efficient persistence.
AU  - Moody, John
DA  - 05/2016
ED  - Ylvisaker, Ben
ID  - 3412
KW  - computers
KW  - graphs
KW  - data
KW  - insectoid creatures
L1  - https://digitalcc.coloradocollege.edu/record/3412/files/High_Performance_Persistent_Graphs_PDF.pdf
L2  - https://digitalcc.coloradocollege.edu/record/3412/files/High_Performance_Persistent_Graphs_PDF.pdf
L4  - https://digitalcc.coloradocollege.edu/record/3412/files/High_Performance_Persistent_Graphs_PDF.pdf
LA  - eng
LK  - https://digitalcc.coloradocollege.edu/record/3412/files/High_Performance_Persistent_Graphs_PDF.pdf
N2  - Persistent data structures allow large and complex data structures to be copied and manipulated inexpensively. The persistent way of representing data offers opportunities to more elegantly and more efficiently implement certain algorithms and programming patterns. Few persistent data structure libraries, however, are designed with an emphasis on speed and performance compared to their mutable cousins. We describe and present a C library for a persistent graph data structure, which uses array compression techniques and balanced wide-fanout tries to create a structure that enables persistence without sacrificing performance. Compared to a competitive C++ mutable graph library, we consistently achieve 30-40% slower random read performance using up to 30% fewer bytes in memory, with the benefit of highly space-efficient persistence.
PY  - 05/2016
T1  - High Performance Persistent Graphs
TI  - High Performance Persistent Graphs
UR  - https://digitalcc.coloradocollege.edu/record/3412/files/High_Performance_Persistent_Graphs_PDF.pdf
ER  -