Concepts and capabilities of a database computer\

Banerjee, Jayanta; Hsiao, David K.; Baum, Richard I.

doi:10.1145/320289.320292

“…IBM has since reported improved performance and scalability for Blue Matter; by interpolation of performance results published recently 3 In our hands, NAMD actually simulated DHFR more slowly on 512 processor cores than on 256. We used NAMD version 2.6b1 for these experiments; more recent versions of NAMD incorporate performance improvements (J. Phillips, personal communication).…”

Section: Performance Comparison To Other MD Platformsmentioning

confidence: 59%

“…After all, history is littered with the corpses of specialized machines, spanning a huge gamut from Lisp machines [20] to database accelerators [3]. Performance and transistor count gains predicted by Moore's law, together with the economies of scale behind the development of commodity processors, have driven a history of general-purpose microprocessors outpacing special-purpose solutions.…”

Section: Why Specialized Hardware?mentioning

confidence: 99%

Anton, a special-purpose machine for molecular dynamics simulation

Shaw

¹

,

Deneroff

²

,

Dror

³

et al. 2007

SIGARCH Comput. Archit. News

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The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macromolecules could in principle provide answers to some of the most important currently outstanding questions in the fields of biology, chemistry and medicine. A wide range of biologically interesting phenomena, however, occur over time scales on the order of a millisecond-about three orders of magnitude beyond the duration of the longest current MD simulations.In this paper, we describe a massively parallel machine called Anton, which should be capable of executing millisecondscale classical MD simulations of such biomolecular systems. The machine, which is scheduled for completion by the end of 2008, is based on 512 identical MD-specific ASICs that interact in a tightly coupled manner using a specialized high-speed communication network. Anton has been designed to use both novel parallel algorithms and special-purpose logic to dramatically accelerate those calculations that dominate the time required for a typical MD simulation. The remainder of the simulation algorithm is executed by a programmable portion of each chip that achieves a substantial degree of parallelism while preserving the flexibility necessary to accommodate anticipated advances in physical models and simulation methods.

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“…This compares to a maximum benchmark parameter simulation rate of 14 ns/day for NAMD on our cluster (using 256 processor cores on 128 cluster nodes 3 ). In other words, we expect Anton to exceed by a factor of nearly 500 the fastest simulation rate currently achievable using generally available codes on commodity hardware.…”

Section: Performance Comparison To Other MD Platformsmentioning

confidence: 99%

Anton, a special-purpose machine for molecular dynamics simulation

Shaw

¹

,

Deneroff

²

,

Dror

³

et al. 2007

Proceedings of the 34th Annual International Symposium on Computer Architecture

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The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macromolecules could in principle provide answers to some of the most important currently outstanding questions in the fields of biology, chemistry and medicine. A wide range of biologically interesting phenomena, however, occur over time scales on the order of a millisecond-about three orders of magnitude beyond the duration of the longest current MD simulations.In this paper, we describe a massively parallel machine called Anton, which should be capable of executing millisecondscale classical MD simulations of such biomolecular systems. The machine, which is scheduled for completion by the end of 2008, is based on 512 identical MD-specific ASICs that interact in a tightly coupled manner using a specialized high-speed communication network. Anton has been designed to use both novel parallel algorithms and special-purpose logic to dramatically accelerate those calculations that dominate the time required for a typical MD simulation. The remainder of the simulation algorithm is executed by a programmable portion of each chip that achieves a substantial degree of parallelism while preserving the flexibility necessary to accommodate anticipated advances in physical models and simulation methods.

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“…Another way to model the mass-storage device is to consider a modified movinghead disk that provides for parallel read/ write of tracks on the same cylinder ( Figure 17). Disks that provide this capability have been proposed [Banerjee et al 1978] and, in some cases, already built. The idea was pioneered by database machine designers, and prototypes have been built in the framework of database research projects (see, e.g., Leilich et al [1978]).…”

Section: Parallel Disk Sortingmentioning

confidence: 99%

A taxonomy of parallel sorting

Bitton

¹

,

DeWitt

²

,

Hsaio

³

et al. 1984

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We propose a taxonomy of parallel sorting that encompasses a broad range of array-and file-sorting algorithms. We analyze how research on parallel sorting has evolved, from the earliest sorting networks to shared memory algorithms and VLSI sorters.In the context of sorting networks, we describe two fundamental parallel merging schemes: the odd-even and the bitonic merge. We discuss sorting algorithms that evolved from these merging schemes for parallel computers, whose processors communicate through interconnection networks such as the perfect shuffle, the mesh, and a number of other sparse networks. Following our discussion of network sorting algorithms, we describe how faster algorithms have been derived from parallel enumeration sorting schemes, where, with a shared memory model of parallel computation, keys are first ranked and then rearranged according to their rank.Parallel sorting algorithms are evaluated according to several criteria related to both the time complexity of an algorithm and its feasibility from the viewpoint of computer architecture. We show that, in addition to attractive communication schemes, network sorting algorithms have nonadaptive schedules that make them suitable for implementation. In particular, they are easily generalized to block sorting algorithms, which utilize limited parallelism to solve large sorting problems. We also address the problem of sorting large mass-storage files in parallel, using modified disk devices or intelligent bubble memory. We conclude by mentioning VLSI sorting as an active and promising direction for research on parallel sorting.

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Concepts and capabilities of a database computer\

Cited by 58 publications

References 15 publications

Anton, a special-purpose machine for molecular dynamics simulation

Anton, a special-purpose machine for molecular dynamics simulation

Anton, a special-purpose machine for molecular dynamics simulation

A taxonomy of parallel sorting

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