TY - JOUR
T1 - Parallelization of general-linkage analysis problems
AU - Dwarkadas, Sandhya
AU - Schäffer, Alejandro A.
AU - Cottingham, Robert W.
AU - Cox, Alan L.
AU - Keleher, Peter
AU - Zwaenepoel, Willy
PY - 1994
Y1 - 1994
N2 - We describe a parallel implementation of a genetic-linkage analysis program that achieves good speed improvement, even for analyses on a single pedigree and with a single starting recombination fraction vector. Our parallel implementation has been run on three different platforms: an Ethernet network of workstations, a higher-bandwidth asynchronous transfer mode (ATM) network of workstations, and a shared-memory multiprocessor. The same program, written in a shared-memory programming style, is used on all platforms. On the workstation networks, the hardware does not provide shared memory, so the program executes on a distributed shared memory system that implements shared memory in software. These three platforms represent different points on the price/performance scale. Ethernet networks are cheap and omnipresent, ATM networks are an emerging technology that offers higher bandwidth, and shared-memory multiprocessors offer the best performance because communication is implemented entirely by hardware. On 8 processors and for the longer runs, we achieve speedups between 3.5 and 5 on the Ethernet network and between 4.8 and 6 on the ATM network. On the shared-memory multiprocessor, we achieve speedups in the 5.5-6.5 range for all runs.
AB - We describe a parallel implementation of a genetic-linkage analysis program that achieves good speed improvement, even for analyses on a single pedigree and with a single starting recombination fraction vector. Our parallel implementation has been run on three different platforms: an Ethernet network of workstations, a higher-bandwidth asynchronous transfer mode (ATM) network of workstations, and a shared-memory multiprocessor. The same program, written in a shared-memory programming style, is used on all platforms. On the workstation networks, the hardware does not provide shared memory, so the program executes on a distributed shared memory system that implements shared memory in software. These three platforms represent different points on the price/performance scale. Ethernet networks are cheap and omnipresent, ATM networks are an emerging technology that offers higher bandwidth, and shared-memory multiprocessors offer the best performance because communication is implemented entirely by hardware. On 8 processors and for the longer runs, we achieve speedups between 3.5 and 5 on the Ethernet network and between 4.8 and 6 on the ATM network. On the shared-memory multiprocessor, we achieve speedups in the 5.5-6.5 range for all runs.
KW - Computational speed improvement
KW - Distributed shared memory
KW - Genetic linkage analysis
KW - Parallel algorithm
KW - Workstation network
UR - http://www.scopus.com/inward/record.url?scp=0028273364&partnerID=8YFLogxK
U2 - 10.1159/000154205
DO - 10.1159/000154205
M3 - Article
C2 - 8039796
AN - SCOPUS:0028273364
SN - 0001-5652
VL - 44
SP - 127
EP - 141
JO - Human Heredity
JF - Human Heredity
IS - 3
ER -