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Scioto, or Shared Collections of Task Objects, is a lightweight framework for providing task management on distributed memory machines under one-sided and global-view parallel programming models. Scioto provides locality aware dynamic load balancing and interoperates with MPI, ARMCI, and Global Arrays. Through task parallelism, the Scioto framework provides a solution for overcoming irregularity, load imbalance, and heterogeneity as well as dynamic mapping of computation onto emerging architectures.


Scioto Programming Model

Scioto provides the user with a task pool programming model. Under this model the user expresses their computation as a set of tasks that can be executed in parallel. Tasks read inputs from their task descriptor as well as from data stored in the global address space. Tasks store their output in the global address space and are also permitted to add new tasks to the task collection.

Below is pseudocode that shows the structure of a simple Scioto program.

 // The user decides how to store task arguments within the task
 // body.  Generally, users define a struct to organize this data.
 typedef struct {
   double args;
 } mytask_t;

 // The user provides a function that implements the task.  This
 // function is run by Scioto when executing the task.
 void task_fcn(gtc_t gtc, task_t *my_task) {
   // ...

 int main() {
   gtc_t    tc   = gtc_create(...);      // Create a task collection
   task_t   task = gtc_task_create(...); // Create a task descriptor
   mytask_t my_t = gtc_task_body(task);  // Get the task body
   my_t.args = ...;    // Fill in the task's arguments

   gtc_task_add(task); // Add the task to the task collection

   gtc_process(tc);    // Enter task-parallel region


Programming Interface

Documentation on Scioto's user API can be found here: Scioto API


Scalable Work Stealing PDF PPT
James Dinan, Sriram Krishnamoorthy, D. Brian Larkins, Jarek Nieplocha, P. Sadayappan
Proc. 21st Intl. Conference on Supercomputing (SC). Portland, OR, Nov. 14-20, 2009.

Scioto: A Framework for Global-View Task Parallelism PDF PPT
James Dinan, Sriram Krishnamoorthy, D. Brian Larkins, Jarek Nieplocha, P. Sadayappan
Proc. of 37th Intl. Conference on Parallel Processing. Portland, OR, Sept. 8-12, 2008.


Project Leaders



This research was supported in part by DOE grant #DE-FC02-06ER25755 and NSF grant #0403342.


Please see the included README file for installation instructions. If you have questions or comments, contact Jim Dinan (dinan at

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