Benchmarking advanced architecture computers

Recently, a number of advanced architecture machines have become commercially available. These new machines promise better cost performance than traditional computers, and some of them have the potential of competing with current supercomputers, such as the CRAY X‐MP, in terms of maximum performance. This paper describes the methodology and results of a pilot study of the performance of a broad range of advanced architecture computers using a number of complete scientific application programs. The computers evaluated include: 1. shared‐memory bus architecture machines such as the Alliant FX/8, the Encore Multimax, and the Sequent Balance and Symmetry 2. shared‐memory network‐connected machines such as the Butterfly 3. distributed‐memory machines such as the NCUBE, Intel and Jet Propulsion Laboratory (JPL)/Caltech hypercubes 4. very long instruction word machines such as the Cydrome Cydra‐5 5. SIMD machines such as the Connection Machine 6. ‘traditional’ supercomputers such as the CRAY X‐MP, CRAY‐2 and SCS‐40. Seven application codes from a number of scientific disciplines have been used in the study, although not all the codes were run on every machine. The methodology and guidelines for establishing a standard set of benchmark programs for advanced architecture computers are discussed. The CRAYs offer the best performance on the benchmark suite; the shared memory multiprocessor machines generally permitted some parallelism, and when coupled with substantial floating point capabilities (as in the Alliant FX/8 and Sequent Symmetry), provided an order of magnitude less speed than the CRAYs. Likewise, the early generation hypercubes studied here generally ran slower than the CRAYs, but permitted substantial parallelism from each of the application codes

Benchmarking advanced architecture computers

Recently, a number of advanced architecture machines have become commercially available. These new machines promise better cost performance than traditional computers, and some of them have the potential of competing with current supercomputers, such as the CRAY X‐MP, in terms of maximum performance. This paper describes the methodology and results of a pilot study of the performance of a broad range of advanced architecture computers using a number of complete scientific application programs. The computers evaluated include: 1. shared‐memory bus architecture machines such as the Alliant FX/8, the Encore Multimax, and the Sequent Balance and Symmetry 2. shared‐memory network‐connected machines such as the Butterfly 3. distributed‐memory machines such as the NCUBE, Intel and Jet Propulsion Laboratory (JPL)/Caltech hypercubes 4. very long instruction word machines such as the Cydrome Cydra‐5 5. SIMD machines such as the Connection Machine 6. ‘traditional’ supercomputers such as the CRAY X‐MP, CRAY‐2 and SCS‐40. Seven application codes from a number of scientific disciplines have been used in the study, although not all the codes were run on every machine. The methodology and guidelines for establishing a standard set of benchmark programs for advanced architecture computers are discussed. The CRAYs offer the best performance on the benchmark suite; the shared memory multiprocessor machines generally permitted some parallelism, and when coupled with substantial floating point capabilities (as in the Alliant FX/8 and Sequent Symmetry), provided an order of magnitude less speed than the CRAYs. Likewise, the early generation hypercubes studied here generally ran slower than the CRAYs, but permitted substantial parallelism from each of the application codes

Retrospective and prospective model simulations of sea level rise impacts on Gulf of Mexico coastal marshes and forests in Waccasassa Bay, Florida

The State of Florida (USA) is especially threatened by sea level rise due to extensive low elevation coastal habitats (approximately 8,000 km2 \u3c 1 m above sea level) where the majority of the human population resides. We used the Sea Level Affecting Marshes Model (SLAMM) simulation to improve understanding of the magnitude and location of these changes for 58,000 ha of the Waccasassa Bay region of Florida’s central Gulf of Mexico coast. To assess how well SLAMM portrays changes in coastal wetland systems resulting from sea level rise, we conducted a hindcast in which we compared model results to 30 years of field plot data. Overall, the model showed the same pattern of coastal forest loss as observed. Prospective runs of SLAMM using 0.64 m, 1 m and 2 m sea level rise scenarios predict substantial changes over this century in the area covered by coastal wetland systems including net losses of coastal forests (69%, 83%, and 99%, respectively) and inland forests (33%, 50%, and 88%), but net gains of tidal flats (17%, 142%, and 3,837%). One implication of these findings at the site level is that undeveloped, unprotected lands inland from the coastal forest should be protected to accommodate upslope migration of this natural community in response to rising seas. At a broader scale, our results suggest that coastal wetland systems will be unevenly affected across the Gulf of Mexico as sea level rises. Species vulnerable to these anticipated changes will experience a net loss or even elimination