在MATLAB中缓慢的xlsread [英] Slow xlsread in MATLAB
问题描述
这是MATLAB程序仿真运行的结果。
Here is the result of a profiled simulation run of my MATLAB program. I need to run this simulation several hundred thousand times (~100,000 times).
因此，我需要一个更快的方式来阅读Excel文件。
Thus I need a faster way to read the Excel file.
规格：Excel文件为10000x2个单元格，每个模拟运行都是从5个单独的Excel文件中读取一张此类表单。
Specifications: The Excel file is of 10000x2 cells and each simulation run is reading one such sheet each from 5 separate Excel files.
更新：我将xlsread置于基本模式，并通过将输入组合到一个文件中来减少呼叫次数。下一个目标是xlswrite。啊，那下沉的感觉：|
UPDATE: I put the xlsread in basic mode and also reduced the number of calls by combining my input into a single file. Next target is xlswrite now. Ah, that sinking feeling. :|
注意：虽然写入 CSV 文件使用dlmread非常快（大约20次），我需要使用.xls文件提供的单独的工作表。
NOTE: Although writing to a CSV file using dlmread is very fast (around 20 times), I need to use the comfort of separate sheets that an .xls file provides.
推荐答案
如果您需要 Excel表格作为输出，我认为您无法从xlswrite中获取更多收益。
I don't think you would be able to wring much out of xlswrite if you need Excel sheets as the output.
如何并行化？
您是否可以访问并行计算工具箱？或者你可以运行两个MATLAB实例，如果你的框支持它。如果是，您可以考虑两种方法：
Do you have access to the parallel computing toolbox? Or maybe you can run two instances of MATLAB if your box supports it. If so, you could consider two approaches:
-
让第一个进程执行xlsread部分，模拟部分然后写入垫文件/纯二进制/ CSV，无论是最快的还是保持数据完整性。有另一个进程使用xlswrite将matfiles /中间数据文件转换成Excel。
Have the first process do the xlsread part, the simulation part and then write to mat files/plain binary/CSV, whatever is the fastest while preserving your data integrity. Have another process convert the matfiles/intermediate data files into Excel using xlswrite.
有N个MATLAB实例/工作人员（N取决于您的物理机容量）。将N个工作人员的整个读取过程写入部分并行化。注意，我不知道Excel工作人员调用时Excel会如何缩放！ （xlswrite使用activeX / MS Excel写入数据）。
Have N MATLAB instances/workers (N depends on your physical machine capacity). Parallelize the whole read-process-write part across N workers. Note, I am not sure how Excel would scale when called by N workers! (xlswrite uses activeX/MS Excel to write the data).
如果使用任何并行方法，您的里程将会有所不同模拟的复杂性与所需的文件I / O及其性能。
As any parallel approach, your mileage will vary on the complexity of the simulation vs. required file I/O and its performance.
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