![]() ![]() The global address space is used to simplify programming, especially on applications with irregular data structures that lead to fine-grained sharing between threads. In addition, there is one additional potential issue to be aware of: virtual memory limits in interactive salloc sessions.Unified Parallel C (UPC) is a parallel language that uses a Single Program Multiple Data (SPMD) model of parallelism within a global address space. PGAS_MEMINFO_DISPLAY: Can be set to 1 in order to enable diagnostic output at launch regarding memory utilization.XT_SYMMETRIC_HEAP_SIZE: Limits the size of the symmetric heap used to service shared memory allocations, analogous to BUPC's UPC_SHARED_HEAP_SIZE. ![]() Specifically, two key environment variables introduced there are: ![]() ![]() To enable UPC support in your C code, simply switch to the Cray compiler environment and supply the -h upc option when calling cc.īecause of its dependence on Cray's PGAS runtime, you may find the additional documentation available on the intro_pgas man page valuable. UPC is directly supported under Cray's compiler environment through their PGAS runtime library (providing similar performance-enabling RDMA functionality to GASNet). UPCR: UPC thread 1 of 4 on nid00705 (pshm node 0 of 2, process 1 of 4, pid = 12391 ) UPCR: UPC thread 3 of 4 on nid00707 (pshm node 1 of 2, process 3 of 4, pid = 33269 ) UPCR: UPC thread 0 of 4 on nid00705 (pshm node 0 of 2, process 0 of 4, pid = 12390 ) UPCR: UPC thread 2 of 4 on nid00707 (pshm node 1 of 2, process 2 of 4, pid = 33268 ) Algorithm: generate random points in x and measure the fraction // of them falling in a circle centered at the origin (approximates pi/4) #include #include #include #include int hit () Ĭori$ salloc -N 2 -t 10:00 -qos =interactive -C haswell Compute pi by approximating the area of a circle of radius 1. First, consider the following UPC source file: If you encounter errors related to shared memory allocation, you will likely want to start by adjusting this quantity.Ĭompiling and running a simple application with BUPC on Cori is fairly straightforward. This size can be controlled via the UPC_SHARED_HEAP_SIZE envvar, or the -shared-heap flag to upcc or upcrun. One of the most important settings is the size of the shared symmetric heap used to service shared memory allocations. Both upcc and upcrun have -help options and man pages describing these. There are a number of flags and environment variables that affect the execution environment of your UPC application compiled with BUPC, all of which can be found in the BUPC documentation. Further, all three supported programming environments on Cori (Intel, GNU, and Cray) are supported by BUPC for use as the underlying C compiler. The latter is able to take advantage of advanced communications functionality of the Cray Aries interconnect on Cori, such as remote direct memory access (RDMA).īUPC is available via the bupc module on Cori, which provides both the upcc compiler wrapper, as well as the upcrun launcher wrapper (which correctly initializes the environment and calls srun). Berkeley UPC ¶īerkeley UPC (BUPC) provides a portable UPC programming environment consisting of a source translation front-end (which in turn relies on a user-supplied C compiler underneath) and a runtime library based on GASNet. UPC is supported on NERSC systems through two different implementations: Berkeley UPC and Cray UPC. Here is a good training video tutorial on UPC. The Berkeley UPC project is one implementation. UPC uses a Single Program Multiple Data (SPMD) model of computation in which the amount of parallelism is fixed at program startup time, typically with a single thread of execution per processor. The programmer is presented with a single shared, partitioned address space, where variables may be directly read and written by any processor, but each variable is physically associated with a single processor. The language provides a uniform programming model for both shared and distributed memory hardware. Unified Parallel C (UPC) is an extension of the C programming language designed for high performance computing on large-scale parallel machines. ![]()
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