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Figure 1 shows the resulting kernel timeline on a Macbook Pro with an NVIDIA GeForce GT 750M (a Kepler GPU). We can run the program in the NVIDIA Visual Profiler ( nvvp) to get a timeline showing all streams and kernel launches. launch a dummy kernel on the default streamįirst let’s check out the legacy behavior, by compiling with no options. As an example of how the legacy default stream causes serialization, we add dummy kernel launches on the default stream that do no work. We launch only a single thread block for each grid so there are plenty of resources to run multiple of them concurrently.
#NEWSTREAM ENTERPRISES DEF TANK ASSEMBLY CODE#
The following code simply launches eight copies of a simple kernel on eight streams. cu file when the code is compiled by nvcc because nvcc implicitly includes cuda_runtime.h at the top of the translation unit. It is important to note: you cannot use #define CUDA_API_PER_THREAD_DEFAULT_STREAM to enable this behavior in a. To enable per-thread default streams in CUDA 7 and later, you can either compile with the nvcc command-line option -default-stream per-thread, or #define the CUDA_API_PER_THREAD_DEFAULT_STREAM preprocessor macro before including CUDA headers ( cuda.h or cuda_runtime.h). This means that commands in the default stream may run concurrently with commands in non-default streams. Second, these default streams are regular streams. This means that commands issued to the default stream by different host threads can run concurrently. First, it gives each host thread its own default stream. As the section “Implicit Synchronization” in the CUDA C Programming Guide explains, two commands from different streams cannot run concurrently if the host thread issues any CUDA command to the default stream between them.ĬUDA 7 introduces a new option, the per-thread default stream, that has two effects. Before CUDA 7, each device has a single default stream used for all host threads, which causes implicit synchronization. The default stream is useful where concurrency is not crucial to performance. The following two lines of code both launch a kernel on the default stream. Specifying a stream for a kernel launch or host-device memory copy is optional you can invoke CUDA commands without specifying a stream (or by setting the stream parameter to zero).
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Memory copies performed by functions with the Async suffix.
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Memory copies from host to device of a memory block of 64 KB or less.Memory copies between two addresses to the same device memory.In this post I’ll show you how this can simplify achieving concurrency between kernels and data copies in CUDA programs.Īs described by the CUDA C Programming Guide, asynchronous commands return control to the calling host thread before the device has finished the requested task (they are non-blocking). Before CUDA 7, the default stream is a special stream which implicitly synchronizes with all other streams on the device.ĬUDA 7 introduces a ton of powerful new functionality, including a new option to use an independent default stream for every host thread, which avoids the serialization of the legacy default stream. When you execute asynchronous CUDA commands without specifying a stream, the runtime uses the default stream. Different streams may execute their commands concurrently or out of order with respect to each other. CUDA Applications manage concurrency by executing asynchronous commands in streams, sequences of commands that execute in order. To do this, applications must execute functions concurrently on multiple processors. Heterogeneous computing is about efficiently using all processors in the system, including CPUs and GPUs.