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Unified Parallel C (UPC) is an extension of the C programming language designed for high performance computing on large-scale parallel machines. The language provides a uniform programming model for both shared and distributed memory hardware. 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. 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 Berkeley UPC project is one implementation.

Here is a good training video tutorial on UPC.


UPC is supported on NERSC systems through two different implementations: Berkeley UPC and Cray UPC.

Berkeley UPC

Berkeley 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. The latter is able to take advantage of advanced communications functionality of the high-speed interconnect of the NERSC systems, such as remote direct memory access (RDMA).

BUPC is available via the bupc module at NERSC which provides both the upcc compiler wrapper, as well as the upcrun launcher wrapper (which correctly initializes the environment and calls srun). Further, all supported programming environments at NERSC are supported by BUPC for use as the underlying C compiler.

On Perlmutter, you first must load the contrib module, which will then make the bupc module available to load:

perlmutter$ module load contrib bupc

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. Both upcc and upcrun have -help options and man pages describing these. One of the most important settings is the size of the shared symmetric heap used to service shared memory allocations. This size can be controlled via the UPC_SHARED_HEAP_SIZE envvar, or the -shared-heap flag to upcc or upcrun. If you encounter errors related to shared memory allocation, you will likely want to start by adjusting this quantity.

Compiling and running a simple application with BUPC at NERSC is fairly straightforward. First, consider the following UPC source file:

// Compute pi by approximating the area of a circle of radius 1. 
// Algorithm: generate random points in [0,1]x[0,1] and measure the fraction 
// of them falling in a circle centered at the origin (approximates pi/4)

#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#include <upc.h>

int hit() { // return non-zero for a hit in the circle
  double x = rand()/(double)RAND_MAX;
  double y = rand()/(double)RAND_MAX;
  return (x*x + y*y) <= 1.0;

// shared array for the results computed by each thread
shared int64_t all_hits[THREADS];

int main(int argc, char **argv) {
    int64_t trials = 100000000;
    if (argc > 1) trials = (int64_t)atoll(argv[1]);
    int64_t my_trials = (trials + THREADS - 1 - MYTHREAD)/THREADS;

    srand(MYTHREAD); // seed each thread's PRNG differently

    int64_t my_hits = 0;
    for (int64_t i=0; i < my_trials; i++)
        my_hits += hit(); // compute in parallel

    all_hits[MYTHREAD] = my_hits; // publish results

    if (MYTHREAD == 0) { // fetch results from each thread
        // (could alternatively call upc_all_reduce())
        int64_t total_hits = 0;
        for (int i=0; i < THREADS; i++)
            total_hits += all_hits[i];
        double pi = 4.0*total_hits/(double)trials;
        printf("PI estimated to %10.7f from %lld trials on %d threads.\n",
               pi, (long long)trials, THREADS);

    return 0;

To compile this file with BUPC:

perlmutter$ module load contrib bupc
perlmutter$ upcc mcpi.upc -o mcpi.x

And then run, in this case in a interactive salloc session:

perlmutter$ salloc -N 2 -t 10:00 --qos=interactive -C cpu
perlmutter$ upcrun -n 4 ./mcpi.x
UPCR: UPC thread 2 of 4 on nid00707 (pshm node 1 of 2, process 2 of 4, pid=33268)
UPCR: UPC thread 0 of 4 on nid00705 (pshm node 0 of 2, process 0 of 4, pid=12390)
UPCR: UPC thread 3 of 4 on nid00707 (pshm node 1 of 2, process 3 of 4, pid=33269)
UPCR: UPC thread 1 of 4 on nid00705 (pshm node 0 of 2, process 1 of 4, pid=12391)
PI estimated to  3.1415196 from 100000000 trials on 4 threads.

Cray UPC

UPC is directly supported under Cray's compiler environment through their PGAS runtime library (providing similar performance-enabling RDMA functionality to GASNet). To enable UPC support in your C code, simply switch to the Cray compiler environment and supply the -h upc option when calling cc.

Because of its dependence on Cray's PGAS runtime, you may find the additional documentation available on the intro_pgas man page valuable. Specifically, two key environment variables introduced there are:

  • 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
  • PGAS_MEMINFO_DISPLAY: Can be set to 1 in order to enable diagnostic output at launch regarding memory utilization.

In addition, there is one additional potential issue to be aware of: virtual memory limits in interactive salloc sessions. If you encounter errors on application launch similar to:

PE 0: ERROR: failed to attach XPMEM segment (at or around line 23 in __pgas_runtime_error_checking() from file ...)

then you may need to release your virtual memory limits by running:

perlmutter$ ulimit -v unlimited

With all of this in mind, compiling and running a simple UPC application, analogous to the above example for BUPC but now using the Cray compilers, would look like:

perlmutter$ module load PrgEnv-cray
perlmutter$ cc -h upc mcpi.upc -o mcpi.x
perlmutter$ salloc -N 2 -t 10:00 --qos=interactive -C haswell
perlmutter$ ulimit -v unlimited  # may not be necessary
perlmutter$ srun -n 4 ./mcpi.x
PI estimated to  3.1414546 from 100000000 trials on 4 threads.