典型的消息代理系统经常将以异步方式处理来自相同流或并行队列的多个请求。
A typical message broker system will often be processing multiple requests from the same stream or queue in a parallel, asynchronous manner.
通常，代码库也引入处理多个版本或者并行地表现不同发布版本的同一段代码流的挑战。
Often, code bases also introduce the challenge of working on multiple versions or streams of the same code that represent different release versions in parallel.
然而，为了让iMic具有适度的性能，我们在本系列文章中的目标是处理两个并行的(立体声)44.1kHz的16位数据流，这就意味着要实现22.05 kHz的音频带宽。
However, in line with the modest capabilities of the iMic, our target for this series is to work with two parallel (stereo) 44.1khz 16-bit data streams, implying an audio bandwidth of 22.05khz.
一个在多个从业者的开发流中并行处理的建模文件。
A modeling file is worked on in parallel in the development streams of multiple practitioners.
这里有一个需要权衡的因素：每个核的线程多有利于并行处理，而线程少能够提高单一处理流的性能。
There’s a trade-off factor in place here: either have more threads per core for concurrent processing or fewer threads, which will ultimately boost single-stream performance.
结构化活动(Structured activity)：用于管理活动序列的整个流程流、活动的并行处理以及在控制流程流时添加条件逻辑。
Structured activities: for managing the overall process flow for sequencing of activities, parallel processing of activities, and adding conditional logic in controlling the process flow.
该模型的特点在于能够有效处理围绕定值输电线路存在并行流的问题，使定值精度有所改进，在此领域取得一定进展。
The model is able to effectively deal with the parallel flow problems around the transmission line, bring improvement in accuracy and some progress in this area.
论文的研究工作着眼于分片式流处理器的数据并行存储系统的分析、设计和实现。
This dissertation focuses on the analysis, design and implementation of data-parallel memory system for Tiled Stream Processor.
与CPU相比，GPU专为高度并行化和密集型的计算而设计，它能使更多的晶体管用于数据处理，而非数据缓存或流控制。
Compared with CPU, GPU was designed for compute-intensive, highly parallel computing, which enabled more transistors to be used for data processing, rather than data caching or flow control.
本文的设计着重从多个层次利用并行处理技术来提高环路滤波的速度，包括流水线设计、数据流驱动控制策略以及算法并行性设计。
Our design emphasizes on using parallel processing technology from multi-level to improve speed, including pipelining design, data-flow drive strategy and algorithmic parallelism design.
倍。CUDA使GPU流处理器阵列的性能得到充分发挥，极大地提高了并行计算程序的效率。
CUDA gives full play to the advantages of GPU Streaming Multiprocessors Array and greatly improves the efficiency of the parallel computation programs.
该方案采用模块化并行多处理器结构，可实现较为复杂的MPEG-2传输流解复用、再复用的过程。
Modular parallel multi-processor architecture is used in this scheme, and de-multiplex and re-multiplex of relatively complicated MPEG-2transport stream can be realized.
尤其在视频图像处理中，需要对大量的高速，并行的视频流数据进行实时处理，FPGA更能发挥其独有的优势。
In particular, the video image processing needs a large number of high-speed, parallel data in real-time video stream processing, FPGA can better play its unique advantage.
该设计应用于FT64流处理器上，使得多个流处理器能够通过高性能网络进行数据传输，以便进行并行流数据运算。
This design is implemented in the FT64 stream processor. By using it, multiple FT64 processors can transfer data through a high-performance network and perform parallel stream computing.
该设计应用于FT64流处理器上，使得多个流处理器能够通过高性能网络进行数据传输，以便进行并行流数据运算。
This design is implemented in the FT64 stream processor. By using it, multiple FT64 processors can transfer data through a high-performance network and perform parallel stream computing.
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