会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明授权
    • Maximized memory throughput using cooperative thread arrays
    • 使用协作线程数组最大化内存吞吐量
    • US07925860B1
    • 2011-04-12
    • US11748298
    • 2007-05-14
    • Norbert JuffaBrett W. Coon
    • Norbert JuffaBrett W. Coon
    • G06F9/30
    • G06F9/3887G06F9/3455G06F9/3851G06F9/3889
    • In parallel processing devices, for streaming computations, processing of each data element of the stream may not be computationally intensive and thus processing may take relatively small amounts of time to compute as compared to memory accesses times required to read the stream and write the results. Therefore, memory throughput often limits the performance of the streaming computation. Generally stated, provided are methods for achieving improved, optimized, or ultimately, maximized memory throughput in such memory-throughput-limited streaming computations. Streaming computation performance is maximized by improving the aggregate memory throughput across the plurality of processing elements and threads. High aggregate memory throughput is achieved by balancing processing loads between threads and groups of threads and a hardware memory interface coupled to the parallel processing devices.
    • 在用于流计算的并行处理装置中,流的每个数据元素的处理可能不是计算密集的,因此与读取流并写入结果所需的存储器访问时间相比,处理可能需要相对较少的时间来计算。 因此,内存吞吐量通常会限制流计算的性能。 一般来说,提供了用于在这种存储器吞吐量限制的流计算中实现改进的,优化的或最终最大化的存储器吞吐量的方法。 通过提高跨多个处理元件和线程的聚合内存吞吐量,最大化流计算性能。 通过平衡线程和线程组之间的处理负载以及耦合到并行处理设备的硬件存储器接口来实现高聚合内存吞吐量。
    • 2. 发明授权
    • Maximized memory throughput on parallel processing devices
    • 最大化并行处理设备的内存吞吐量
    • US08327123B2
    • 2012-12-04
    • US13069384
    • 2011-03-23
    • Norbert JuffaBrett W. Coon
    • Norbert JuffaBrett W. Coon
    • G06F9/30
    • G06F9/3887G06F9/3455G06F9/3851G06F9/3889
    • In parallel processing devices, for streaming computations, processing of each data element of the stream may not be computationally intensive and thus processing may take relatively small amounts of time to compute as compared to memory accesses times required to read the stream and write the results. Therefore, memory throughput often limits the performance of the streaming computation. Generally stated, provided are methods for achieving improved, optimized, or ultimately, maximized memory throughput in such memory-throughput-limited streaming computations. Streaming computation performance is maximized by improving the aggregate memory throughput across the plurality of processing elements and threads. High aggregate memory throughput is achieved by balancing processing loads between threads and groups of threads and a hardware memory interface coupled to the parallel processing devices.
    • 在用于流计算的并行处理装置中,流的每个数据元素的处理可能不是计算密集的,因此与读取流并写入结果所需的存储器访问时间相比,处理可能需要相对较少的时间来计算。 因此,内存吞吐量通常会限制流计算的性能。 一般来说,提供了用于在这种存储器吞吐量限制的流计算中实现改进的,优化的或最终最大化的存储器吞吐量的方法。 通过提高跨多个处理元件和线程的聚合内存吞吐量,最大化流计算性能。 通过平衡线程和线程组之间的处理负载以及耦合到并行处理设备的硬件存储器接口来实现高聚合内存吞吐量。
    • 3. 发明申请
    • MAXIMIZED MEMORY THROUGHPUT ON PARALLEL PROCESSING DEVICES
    • 最大化的并行处理器件的存储器
    • US20110173414A1
    • 2011-07-14
    • US13069384
    • 2011-03-23
    • Norbert JuffaBrett W. Coon
    • Norbert JuffaBrett W. Coon
    • G06F9/38
    • G06F9/3887G06F9/3455G06F9/3851G06F9/3889
    • In parallel processing devices, for streaming computations, processing of each data element of the stream may not be computationally intensive and thus processing may take relatively small amounts of time to compute as compared to memory accesses times required to read the stream and write the results. Therefore, memory throughput often limits the performance of the streaming computation. Generally stated, provided are methods for achieving improved, optimized, or ultimately, maximized memory throughput in such memory-throughput-limited streaming computations. Streaming computation performance is maximized by improving the aggregate memory throughput across the plurality of processing elements and threads. High aggregate memory throughput is achieved by balancing processing loads between threads and groups of threads and a hardware memory interface coupled to the parallel processing devices.
    • 在用于流计算的并行处理装置中,流的每个数据元素的处理可能不是计算密集的,因此与读取流并写入结果所需的存储器访问时间相比,处理可能需要相对较少的时间来计算。 因此,内存吞吐量通常会限制流计算的性能。 一般来说,提供了用于在这种存储器吞吐量限制的流计算中实现改进的,优化的或最终最大化的存储器吞吐量的方法。 通过提高跨多个处理元件和线程的聚合内存吞吐量,最大化流计算性能。 通过平衡线程和线程组之间的处理负载以及耦合到并行处理设备的硬件存储器接口来实现高聚合内存吞吐量。
    • 5. 发明授权
    • Hardware resource based mapping of cooperative thread arrays (CTA) to result matrix tiles for efficient matrix multiplication in computing system comprising plurality of multiprocessors
    • 基于硬件资源的协作线程数组(CTA)的映射结果用于在包括多个多处理器的计算系统中有效的矩阵乘法的矩阵瓦片
    • US07506134B1
    • 2009-03-17
    • US11454542
    • 2006-06-16
    • Norbert JuffaRadoslav Danilak
    • Norbert JuffaRadoslav Danilak
    • G06F9/46
    • G06F9/5066G06F9/5038G06F2209/5017
    • The present invention enables efficient matrix multiplication operations on parallel processing devices. One embodiment is a method for mapping CTAs to result matrix tiles for matrix multiplication operations. Another embodiment is a second method for mapping CTAs to result tiles. Yet other embodiments are methods for mapping the individual threads of a CTA to the elements of a tile for result tile computations, source tile copy operations, and source tile copy and transpose operations. The present invention advantageously enables result matrix elements to be computed on a tile-by-tile basis using multiple CTAs executing concurrently on different streaming multiprocessors, enables source tiles to be copied to local memory to reduce the number accesses from the global memory when computing a result tile, and enables coalesced read operations from the global memory as well as write operations to the local memory without bank conflicts.
    • 本发明使得能够对并行处理装置进行有效的矩阵乘法运算。 一个实施例是用于将CTA映射到用于矩阵乘法运算的矩阵瓦片的方法。 另一个实施例是用于将CTA映射到结果瓦片的第二种方法。 其他实施例是用于将CTA的各个线程映射到块的元素以用于结果瓦片计算,源瓦片复制操作以及源瓦片复制和转置操作的方法。 本发明有利地使结果矩阵元素可以使用在不同的流式多处理器上同时执行的多个CTA来逐个瓦片地计算,使得能够将源瓦片复制到本地存储器,以减少当计算一个 结果图块,并且启用来自全局存储器的合并的读取操作以及对本地存储器的写入操作,而没有存储体冲突。
    • 6. 发明授权
    • Method and apparatus for calculating a power of an operand
    • 用于计算操作数的功率的方法和装置
    • US06381625B2
    • 2002-04-30
    • US09782474
    • 2001-02-12
    • Stuart ObermanNorbert JuffaMing SiuFrederick D WeberRavikrishna Cherukuri
    • Stuart ObermanNorbert JuffaMing SiuFrederick D WeberRavikrishna Cherukuri
    • G06F7552
    • G06F7/53G06F7/4991G06F7/49936G06F7/49963G06F7/49994G06F7/5338G06F7/5443G06F9/30036G06F9/3017G06F9/3804G06F9/3885G06F17/16G06F2207/3828
    • A multiplier capable of performing signed and unsigned scalar and vector multiplication is disclosed. The multiplier is configured to receive signed or unsigned multiplier and multiplicand operands in scalar or packed vector form. An effective sign for the multiplier and multiplicand operands may be calculated and used to create and select a number of partial products according to Booth's algorithm. Once the partial products have been created and selected, they may be summed and the results may be output. The results may be signed or unsigned, and may represent vector or scalar quantities. When a vector multiplication is performed, the multiplier may be configured to generate and select partial products so as to effectively isolate the multiplication process for each pair of vector components. The multiplier may also be configured to sum the products of the vector components to form the vector dot product. The final product may be output in segments so as to require fewer bus lines. The segments may be rounded by adding a rounding constant. Rounding and normalization may be performed in two paths, one assuming an overflow will occur, the other assuming no overflow will occur. The multiplier may also be configured to perform iterative calculations to evaluate constant powers of an operand. Intermediate products that are formed may be rounded and normalized in two paths and then compressed and stored for use in the next iteration. An adjustment constant may also be added to increase the frequency of exactly rounded results.
    • 公开了能够执行有符号和无符号标量和矢量乘法的乘法器。 乘法器配置为以标量或压缩向量形式接收带符号或无符号乘数和被乘数操作数。 可以计算乘数和被乘数操作数的有效符号,并用于根据布斯算法创建和选择多个部分乘积。 一旦创建并选择了部分产品,就可以对它们进行求和并输出结果。 结果可能是有符号或无符号的,可能表示向量或标量。 当执行向量乘法时,乘法器可以被配置为产生和选择部分乘积,以便有效地隔离每对向量分量的乘法过程。 乘法器还可以被配置为对矢量分量的乘积求和以形成向量点积。 最终产品可以分段输出,以便需要更少的总线。 可以通过添加舍入常数来对段进行舍入。 可以在两个路径中执行舍入和归一化,一个假设将发生溢出,另一个假设不会发生溢出。 乘法器还可以被配置为执行迭代计算以评估操作数的恒定功率。 形成的中间产品可以在两个路径中进行圆化和归一化,然后压缩并存储以用于下一次迭代。 还可以添加调整常数以增加精确舍入结果的频率。
    • 8. 发明授权
    • Apparatus and method for using checking instructions in a floating-point execution unit
    • 在浮点执行单元中使用检查指令的装置和方法
    • US06247117B1
    • 2001-06-12
    • US09265230
    • 1999-03-08
    • Norbert Juffa
    • Norbert Juffa
    • G06F1500
    • G06F9/226G06F9/30014G06F9/30192
    • The use of checking instructions to detect special and exceptional cases of a defined data format in a microprocessor is disclosed. Generally speaking, a checking instruction is included with the microcode of floating-point instructions to detect special and exceptional cases of operand values for the floating-point instructions. A checking instruction is configured to set one or more flags in a flags register if it detects a special or exceptional case for an operand value. A checking instruction may also set the result or results of a floating-point instruction to a result value if a special or exceptional case is detected. In addition, a checking instruction may be configured to set one or more bits in status register if a special or exceptional case is detected. After a checking instruction completes execution, a subsequent microcode instruction can be executed to determine if one or more flags were set by the checking instruction. If one or more flags have been set by the checking instruction, the subsequent microcode instruction can branch to a non-sequential microcode instruction to handle the special or exceptional case detected by the checking instruction.
    • 公开了使用检查指令来检测微处理器中定义的数据格式的特殊和异常情况。 一般来说,浮点指令的微码中包含检查指令,以检测浮点指令的操作数值的特殊情况和异常情况。 检查指令被配置为在标志寄存器中设置一个或多个标志,如果它检测到操作数值的特殊或异常情况。 如果检测到特殊或特殊情况,则检查指令还可以将浮点指令的结果或结果设置为结果值。 此外,如果检测到特殊或特殊情况,则检查指令可以被配置为在状态寄存器中设置一个或多个位。 在检查指令完成执行之后,可以执行随后的微代码指令以确定检查指令是否设置了一个或多个标志。 如果通过检查指令设置了一个或多个标志,则后续的微代码指令可以转移到非顺序的微代码指令,以处理由检查指令检测到的特殊或特殊情况。
    • 10. 发明申请
    • EFFICIENT MATRIX MULTIPLICATION ON A PARALLEL PROCESSING DEVICE
    • 并行处理器件的高效矩阵乘法
    • US20100325187A1
    • 2010-12-23
    • US12875961
    • 2010-09-03
    • Norbert JuffaRadoslav Danilak
    • Norbert JuffaRadoslav Danilak
    • G06F7/52
    • G06F17/16
    • The present invention enables efficient matrix multiplication operations on parallel processing devices. One embodiment is a method for mapping CTAs to result matrix tiles for matrix multiplication operations. Another embodiment is a second method for mapping CTAs to result tiles. Yet other embodiments are methods for mapping the individual threads of a CTA to the elements of a tile for result tile computations, source tile copy operations, and source tile copy and transpose operations. The present invention advantageously enables result matrix elements to be computed on a tile-by-tile basis using multiple CTAs executing concurrently on different streaming multiprocessors, enables source tiles to be copied to local memory to reduce the number accesses from the global memory when computing a result tile, and enables coalesced read operations from the global memory as well as write operations to the local memory without bank conflicts.
    • 本发明使得能够对并行处理装置进行有效的矩阵乘法运算。 一个实施例是用于将CTA映射到用于矩阵乘法运算的矩阵瓦片的方法。 另一个实施例是用于将CTA映射到结果瓦片的第二种方法。 其他实施例是用于将CTA的各个线程映射到块的元素以用于结果瓦片计算,源瓦片复制操作以及源瓦片复制和转置操作的方法。 本发明有利地使结果矩阵元素可以使用在不同的流式多处理器上同时执行的多个CTA来逐个瓦片地计算,使得能够将源瓦片复制到本地存储器,以减少当计算一个 结果图块,并且启用来自全局存储器的合并的读取操作以及对本地存储器的写入操作,而没有存储体冲突。