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Support Asynchronous Data Transfers/Overlapping Compute #62

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Support Asynchronous Data Transfers/Overlapping Compute#62
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@GoogleCodeExporter
GoogleCodeExporter
opened on Jul 7, 2015
Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33

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Support Asynchronous Data Transfers/Overlapping Compute · Issue #62 · vaaale/aparapi · GitHub
      Skip to content
      Support Asynchronous Data Transfers/Overlapping Compute #62
      Open
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      Support Asynchronous Data Transfers/Overlapping Compute#62
      Labels
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      Description
      @GoogleCodeExporter
      GoogleCodeExporter
      opened on Jul 7, 2015
      Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

      Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33
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Support Asynchronous Data Transfers/Overlapping Compute · Issue #62 · vaaale/aparapi · GitHub
          Skip to content
          Support Asynchronous Data Transfers/Overlapping Compute #62
          Open
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          Support Asynchronous Data Transfers/Overlapping Compute#62
          Labels
          Priority-MediumType-Enhancementauto-migrated
          Description
          @GoogleCodeExporter
          GoogleCodeExporter
          opened on Jul 7, 2015
          Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

          Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33
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var __m = "*";
var __re = new RegExp('^' + ".*" + '
Support Asynchronous Data Transfers/Overlapping Compute · Issue #62 · vaaale/aparapi · GitHub
              Skip to content
              Support Asynchronous Data Transfers/Overlapping Compute #62
              Open
              Open
              Support Asynchronous Data Transfers/Overlapping Compute#62
              Labels
              Priority-MediumType-Enhancementauto-migrated
              Description
              @GoogleCodeExporter
              GoogleCodeExporter
              opened on Jul 7, 2015
              Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

              Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33
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, 'i');
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try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
Support Asynchronous Data Transfers/Overlapping Compute · Issue #62 · vaaale/aparapi · GitHub
                  Skip to content
                  Support Asynchronous Data Transfers/Overlapping Compute #62
                  Open
                  Open
                  Support Asynchronous Data Transfers/Overlapping Compute#62
                  Labels
                  Priority-MediumType-Enhancementauto-migrated
                  Description
                  @GoogleCodeExporter
                  GoogleCodeExporter
                  opened on Jul 7, 2015
                  Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

                  Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Support Asynchronous Data Transfers/Overlapping Compute · Issue #62 · vaaale/aparapi · GitHub
                      Skip to content
                      Support Asynchronous Data Transfers/Overlapping Compute #62
                      Open
                      Open
                      Support Asynchronous Data Transfers/Overlapping Compute#62
                      Labels
                      Priority-MediumType-Enhancementauto-migrated
                      Description
                      @GoogleCodeExporter
                      GoogleCodeExporter
                      opened on Jul 7, 2015
                      Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

                      Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33
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, 'i');
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Support Asynchronous Data Transfers/Overlapping Compute · Issue #62 · vaaale/aparapi · GitHub
                          Skip to content
                          Support Asynchronous Data Transfers/Overlapping Compute #62
                          Open
                          Open
                          Support Asynchronous Data Transfers/Overlapping Compute#62
                          Labels
                          Priority-MediumType-Enhancementauto-migrated
                          Description
                          @GoogleCodeExporter
                          GoogleCodeExporter
                          opened on Jul 7, 2015
                          Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

                          Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33
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Support Asynchronous Data Transfers/Overlapping Compute · Issue #62 · vaaale/aparapi · GitHub
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                              Support Asynchronous Data Transfers/Overlapping Compute #62
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                              Support Asynchronous Data Transfers/Overlapping Compute#62
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                              Priority-MediumType-Enhancementauto-migrated
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                              @GoogleCodeExporter
                              GoogleCodeExporter
                              opened on Jul 7, 2015
                              Currently, Aparapi only supports synchronous data transfers. OpenCL supports both synchronous and asynchronous data transfers.
Excellent article (by a gentleman who apparently used to work at PNNL):
http://www.codeproject.com/Articles/201258/Part-5-OpenCL-Buffers-and-Memory-Affi
nity
<snip>
"Explicit, programmer initiated transfers occur by queuing one or more transfers on a command queue. Examples include:
C API:
clEnqueueReadBuffer(), clEnqueueReadImage()
clEnqueueWriteBuffer(), clEnqueueWriteImage()
clEnqueueCopyBuffer(), clEnqueueCopyImage()
C++ API
cl::enqueueReadBuffer(), cl::enqueueWriteBuffer()
Data transfers can be either blocking, in which case the queue waits for the transfer to complete, or asynchronous requiring the use of events for notification when a transfer has completed. Using asynchronous data transfers benefits application performance by allowing computation to overlap with data movement - thus decreasing the time to solution. Since the PCIe bus is full duplex, meaning that it can transfer data in two directions at the same time, there is a potential 2-times increase in data transfer bandwidth that can be achieved.
Alternatively, regions of the object data can be implicitly transferred by mapping buffers into the host address space. These transfers can occur both asynchronously and on a demand basis, meaning only portions of the data required by a calculation are moved and cached on a device. API examples include:
C API:
clEnqueueMapBuffer(), clEnqueueMapImage()
clEnqueueUnmapMemObject()
C++ API:
cl::Buffer() (via various flags discussed below)
cl::enqueueMapBuffer(), cl::enqueueMapImage()
cl::enqueueUnmapMemObject();"
There is a lot of great information in that article.

                              Original issue reported on code.google.com by ryan.lam...@gmail.com on 11 Aug 2012 at 10:33
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