Julia [5] [15] is a high-level computing language used by many developers for its performance and ease of use. Julia operates on tasks that are run concurrently on threads. In its current state, however, Julia is not able to effectively employ fine-grained parallelism. OpenCilk [9] is an open-source implementation of the Cilk concurrency platform designed to utilize fine-grain parallelism. The Cilk runtime system, based on Cheetah [12], offers provably efficient parallel scheduling whose performance is borne out in theory and practice. I propose a combination of the Julia and OpenCilk runtimes through the integration of multiple components. One contribution of this thesis is a novel algorithm for combining C/C++ memory allocations with Juli...
Due to power constraints, future growth in computing capability must explicitly leverage parallelism...
Although cost-effective parallel machines are now commercially available, the widespread use of para...
Since processor performance scalability will now mostly be achieved through thread-level parallelism...
This thesis describes Cilk, a parallel multithreaded language for programming contemporary shared me...
In this thesis, I present Multicilk, a threads library based on C11 threads and the OpenCilk runtime...
The increasing proliferation of low-cost microcomputer networks has brought distributed computing wi...
Cilk (pronounced “silk”) is a C-based runtime system for multi-threaded parallel programming. In thi...
Today, almost all desktop and laptop computers are shared-memory multicores, but the code they run i...
This document describes Cilk 5.3.2, a language for multithreaded parallel programming based on ANSI ...
The prevalence of multicore processors is bound to drive most kinds of software development towards ...
The Julia programming language is gaining enormous popularity. Julia was designed to be easy and fas...
The availability of multicore processors across a wide range of computing platforms has created a st...
This document describes Cilk-5.0, a language for multithreaded parallel programming based on ANSI C....
Many multithreaded concurrency platforms that use a work-stealing runtime system incorporate a "cact...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Due to power constraints, future growth in computing capability must explicitly leverage parallelism...
Although cost-effective parallel machines are now commercially available, the widespread use of para...
Since processor performance scalability will now mostly be achieved through thread-level parallelism...
This thesis describes Cilk, a parallel multithreaded language for programming contemporary shared me...
In this thesis, I present Multicilk, a threads library based on C11 threads and the OpenCilk runtime...
The increasing proliferation of low-cost microcomputer networks has brought distributed computing wi...
Cilk (pronounced “silk”) is a C-based runtime system for multi-threaded parallel programming. In thi...
Today, almost all desktop and laptop computers are shared-memory multicores, but the code they run i...
This document describes Cilk 5.3.2, a language for multithreaded parallel programming based on ANSI ...
The prevalence of multicore processors is bound to drive most kinds of software development towards ...
The Julia programming language is gaining enormous popularity. Julia was designed to be easy and fas...
The availability of multicore processors across a wide range of computing platforms has created a st...
This document describes Cilk-5.0, a language for multithreaded parallel programming based on ANSI C....
Many multithreaded concurrency platforms that use a work-stealing runtime system incorporate a "cact...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Due to power constraints, future growth in computing capability must explicitly leverage parallelism...
Although cost-effective parallel machines are now commercially available, the widespread use of para...
Since processor performance scalability will now mostly be achieved through thread-level parallelism...