High-Performance Computing Using FPGAs
High-Performance Computing Using FPGAs
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DOI：
10.1007/978-1-4614-1791-0
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发表时间：
2013-05
期刊：
影响因子：
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通讯作者：
W. Vanderbauwhede;K. Benkrid
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文献类型：
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作者：
W. Vanderbauwhede;K. Benkrid
在本章中，我们将介绍Janus超级计算机，这是一个基于FPGA的大规模并行系统，用于模拟自旋玻璃，描述玻璃状材料行为的理论模型。Janus的自定义架构已经开发出来，以满足这些模型的计算要求。自旋玻璃模拟是使用蒙特卡罗方法进行的，该方法产生的算法具有以下特征：（1）固有的并行性，允许我们在单个FPGA中实现许多蒙特卡罗更新引擎;（2）可以存储在片上的相当小的数据库（2 MB），显着提高带宽并减少延迟。(3)需要产生大量质量好的长（≥ 32位）随机数;（4）多为整数算术和按位逻辑运算。根据这些算法的特定功能仔细定制架构，使我们能够在一个FPGA中嵌入多达1024个专用核心，因此可以在短短几个月内执行传统架构上需要几个世纪的系统模拟。
In this chapter we describe the Janus supercomputer, a massively parallel FPGA-based system optimized for the simulation of spin-glasses, theoretical models that describe the behavior of glassy materials. The custom architecture of Janus has been developed to meet the computational requirements of these models. Spin-glass simulations are performed using Monte Carlo methods that lead to algorithms characterized by (1) intrinsic parallelism allowing us to implement many Monte Carlo update engines within a single FPGA; (2) rather small data base (2 MByte) that can be stored on-chip, significantly boosting bandwidth and reducing latency. (3) need to generate a large number of good-quality long (≥ 32 bit) random numbers; (4) mostly integer arithmetic and bitwise logic operations. Careful tailoring of the architecture to the specific features of these algorithms has allowed us to embed up to 1024 special purpose cores within just one FPGA, so that simulations of systems that would take centuries on conventional architectures can be performed in just a few months.