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    • 64. 发明授权
    • Data eye monitor method and apparatus
    • 数据眼监护仪方法及装置
    • US08108738B2
    • 2012-01-31
    • US11768810
    • 2007-06-26
    • Alan G. GaraJames A. MarcellaMartin Ohmacht
    • Alan G. GaraJames A. MarcellaMartin Ohmacht
    • G06K5/04G11B5/00G11B20/20
    • G06F13/1689
    • An apparatus and method for providing a data eye monitor. The data eye monitor apparatus utilizes an inverter/latch string circuit and a set of latches to save the data eye for providing an infinite persistent data eye. In operation, incoming read data signals are adjusted in the first stage individually and latched to provide the read data to the requesting unit. The data is also simultaneously fed into a balanced XOR tree to combine the transitions of all incoming read data signals into a single signal. This signal is passed along a delay chain and tapped at constant intervals. The tap points are fed into latches, capturing the transitions at a delay element interval resolution. Using XORs, differences between adjacent taps and therefore transitions are detected. The eye is defined by segments that show no transitions over a series of samples. The eye size and position can be used to readjust the delay of incoming signals and/or to control environment parameters like voltage, clock speed and temperature.
    • 一种用于提供数据眼监护仪的装置和方法。 数据眼监视装置利用逆变器/锁存器串电路和一组锁存器来保存数据,以提供无限持续数据眼。 在操作中,输入的读数据信号在第一阶段被单独地调整并被锁存以将读取的数据提供给请求单元。 数据也被同时馈送到平衡XOR树中,以将所有输入的读取数据信号的转换组合成单个信号。 该信号沿着延迟链传递,并以恒定间隔敲击。 抽头点被馈送到锁存器,以延迟元件间隔分辨率捕获转换。 使用XOR,检测相邻抽头之间的差异,因此检测到转换之间的差异。 眼睛由在一系列样本上没有显示转换的片段定义。 眼睛大小和位置可用于重新调整输入信号的延迟和/或控制环境参数,如电压,时钟速度和温度。
    • 65. 发明授权
    • Efficient implementation of multidimensional fast fourier transform on a distributed-memory parallel multi-node computer
    • 在分布式存储并行多节点计算机上高效实现多维快速傅里叶变换
    • US08095585B2
    • 2012-01-10
    • US11931898
    • 2007-10-31
    • Gyan V. BhanotDong ChenAlan G. GaraMark E. GiampapaPhilip HeidelbergerBurkhard D. Steinmacher-BurowPavlos M. Vranas
    • Gyan V. BhanotDong ChenAlan G. GaraMark E. GiampapaPhilip HeidelbergerBurkhard D. Steinmacher-BurowPavlos M. Vranas
    • G06F17/14
    • H05K7/20836F24F11/77G06F9/52G06F9/526G06F15/17381G06F17/142G09G5/008H04L7/0338
    • The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via “all-to-all” distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The “all-to-all” re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.
    • 发明内容涉及一种用于有效地实现多维阵列的多维快速傅里叶变换(FFT)的方法,系统和程序存储设备,所述多维阵列包括最初分布在多节点计算机系统中的多个元素,所述多节点包括多个节点 通过网络进行通信,包括:通过所述网络在所述计算机系统的所述多个节点之间以第一维度分布所述阵列的所述多个元素以促进第一一维FFT; 对分布在第一维度中的每个节点的阵列的元素执行第一个一维FFT; 通过网络上的计算机系统的其他节点以随机顺序的“全对全”分布,在第二维度中的每个节点处重新分布一维FFT变换的元素; 以及对在所述第二维度中的每个节点处重新分布的阵列的元素执行第二一维FFT,其中所述随机顺序有助于所述网络的有效利用,从而有效地实现所述多维FFT。 在分布式存储器并行超级计算机上的多维FFT以外的应用中,数组元素的“全部”重新分配进一步有效地实现。
    • 68. 发明授权
    • Low latency memory access and synchronization
    • 低延迟内存访问和同步
    • US07818514B2
    • 2010-10-19
    • US12196796
    • 2008-08-22
    • Matthias A. BlumrichDong ChenPaul W. CoteusAlan G. GaraMark E. GiampapaPhilip HeidelbergerDirk HoenickeMartin OhmachtBurkhard D. Steinmacher-BurowTodd E. TakkenPavlos M. Vranas
    • Matthias A. BlumrichDong ChenPaul W. CoteusAlan G. GaraMark E. GiampapaPhilip HeidelbergerDirk HoenickeMartin OhmachtBurkhard D. Steinmacher-BurowTodd E. TakkenPavlos M. Vranas
    • G06F12/06
    • G06F12/0862G06F9/52G06F2212/6028
    • A low latency memory system access is provided in association with a weakly-ordered multiprocessor system. Bach processor in the multiprocessor shares resources, and each shared resource has an associated lock within a locking device that provides support for synchronization between the multiple processors in the multiprocessor and the orderly sharing of the resources. A processor only has permission to access a resource when it owns the lock associated with that resource, and an attempt by a processor to own a lock requires only a single load operation, rather than a traditional atomic load followed by store, such that the processor only performs a read operation and the hardware locking device performs a subsequent write operation rather than the processor. A simple prefetching for non-contiguous data structures is also disclosed. A memory line is redefined so that in addition to the normal physical memory data, every line includes a pointer that is large enough to point to any other line in the memory, wherein the pointers to determine which memory line to prefetch rather than some other predictive algorithm. This enables hardware to effectively prefetch memory access patterns that are non-contiguous, but repetitive.
    • 与弱有序的多处理器系统相关联地提供低延迟存储器系统访问。 多处理器中的Bach处理器共享资源,并且每个共享资源在锁定设备内具有关联的锁,其提供对多处理器中的多个处理器之间的同步的支持以及资源的有序共享。 当处理器拥有与该资源相关联的锁定时,处理器仅具有访问资源的权限,并且处理器拥有锁的尝试仅需要单个加载操作,而不是传统的原子负载后跟存储,使得处理器 只执行读取操作,并且硬件锁定装置执行后续的写入操作而不是处理器。 还公开了用于非连续数据结构的简单预取。 重新定义存储器线,使得除了正常的物理存储器数据之外,每行包括足够大的指针以指向存储器中的任何其他行,其中指针用于确定要预取的存储器行而不是一些其它预测 算法。 这使得硬件能够有效地预取不连续但重复的存储器访问模式。
    • 70. 发明申请
    • NOVEL MASSIVELY PARALLEL SUPERCOMPUTER
    • 新的大型并行超级计算机
    • US20090259713A1
    • 2009-10-15
    • US12492799
    • 2009-06-26
    • Matthias A. BlumrichDong ChenGeorge L. ChiuThomas M. CipollaPaul W. CoteusAlan G. GaraMark E. GiampapaPhilip HeidelbergerGerard V. KopcsayLawrence S. MokTodd E. Takken
    • Matthias A. BlumrichDong ChenGeorge L. ChiuThomas M. CipollaPaul W. CoteusAlan G. GaraMark E. GiampapaPhilip HeidelbergerGerard V. KopcsayLawrence S. MokTodd E. Takken
    • G06F15/76G06F15/16G06F11/28G06F12/08G06F9/02G06F15/177
    • H05K7/20836F24F11/77G06F9/52G06F9/526G06F15/17381G06F17/142G09G5/008H04L7/0338
    • A novel massively parallel supercomputer of hundreds of teraOPS-scale includes node architectures based upon System-On-a-Chip technology, i.e., each processing node comprises a single Application Specific Integrated Circuit (ASIC). Within each ASIC node is a plurality of processing elements each of which consists of a central processing unit (CPU) and plurality of floating point processors to enable optimal balance of computational performance, packaging density, low cost, and power and cooling requirements. The plurality of processors within a single node may be used individually or simultaneously to work on any combination of computation or communication as required by the particular algorithm being solved or executed at any point in time. The system-on-a-chip ASIC nodes are interconnected by multiple independent networks that optimally maximizes packet communications throughput and minimizes latency. In the preferred embodiment, the multiple networks include three high-speed networks for parallel algorithm message passing including a Torus, Global Tree, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. For particular classes of parallel algorithms, or parts of parallel calculations, this architecture exhibits exceptional computational performance, and may be enabled to perform calculations for new classes of parallel algorithms. Additional networks are provided for external connectivity and used for Input/Output, System Management and Configuration, and Debug and Monitoring functions. Special node packaging techniques implementing midplane and other hardware devices facilitates partitioning of the supercomputer in multiple networks for optimizing supercomputing resources.
    • 数百个teraOPS级别的新型大规模并行超级计算机包括基于片上系统技术的节点架构,即每个处理节点包括单个专用集成电路(ASIC)。 在每个ASIC节点内是多个处理元件,每个处理元件由中央处理单元(CPU)和多个浮点处理器组成,以实现计算性能,封装密度,低成本以及功率和冷却​​要求的最佳平衡。 单个节点内的多个处理器可以单独使用或同时使用,以在任何时间点解决或执行的特定算法所要求的任何计算或通信组合上工作。 片上系统ASIC节点通过多个独立网络互连,从而最大限度地最大限度地提高了分组通信吞吐量并最大限度地减少了延迟。 在优选实施例中,多个网络包括用于并行算法消息传递的三个高速网络,包括提供全局障碍和通知功能的环形,全局树和全球异步网络。 这些多个独立网络可以根据用于优化算法处理性能的算法的需求或阶段来协同或独立地利用。 对于特定类别的并行算法或并行计算的部分,该架构具有出色的计算性能,并且可以启用对新类并行算法执行计算。 为外部连接提供附加网络,用于输入/输出,系统管理和配置以及调试和监控功能。 实现中平面和其他硬件设备的特殊节点打包技术有助于在多个网络中划分超级计算机,以优化超级计算资源。