Computer architecture has looming challenges with finding program parallelism, process technology limits, and limited power budget. To navigate these challenges, a deeper understanding of parallel programs is required. I will discuss the task graph representation and how it enables programmers and compiler optimizations to understand and exploit dynamic aspects of the program. I will present Contech, which is a high performance framework for generating dynamic task graphs from arbitrary parallel programs. The Contech framework supports a variety of languages and parallelization libraries, and has been tested on both x86 and ARM. I will demonstrate how this framework encompasses a diversity of program analyses, particularly by modeling a dy...
One of the major current challenges in computer science is providing program-ming models and abstrac...
As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as paral...
For a wide variety of applications, both task and data parallelism must be exploited to achieve the ...
It has become common knowledge that parallel programming is needed for scientific applications, part...
The end of Dennard scaling also brought an end to frequency scaling as a means to improve performanc...
It has become common knowledge that parallel programming is needed for scientific applications, part...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Performance analysis of parallel programs continues to be challenging for programmers. Programmers h...
Today’s processors exploit the fine grain data parallelism that exists in many applications via ILP ...
Programming abstractions to simplify distributed parallel computing have been widely adopted. Yet, i...
While the chip multiprocessor (CMP) has quickly become the predominant processor architecture, its c...
The relative ease with which it is possible to build inexpensive, high-performance multicomputers u...
The relative ease with which it is possible to build inexpensive, high-performance multicomputers u...
There is an increasing need for a framework that supports research on portable high-performance para...
As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as paral...
One of the major current challenges in computer science is providing program-ming models and abstrac...
As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as paral...
For a wide variety of applications, both task and data parallelism must be exploited to achieve the ...
It has become common knowledge that parallel programming is needed for scientific applications, part...
The end of Dennard scaling also brought an end to frequency scaling as a means to improve performanc...
It has become common knowledge that parallel programming is needed for scientific applications, part...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Performance analysis of parallel programs continues to be challenging for programmers. Programmers h...
Today’s processors exploit the fine grain data parallelism that exists in many applications via ILP ...
Programming abstractions to simplify distributed parallel computing have been widely adopted. Yet, i...
While the chip multiprocessor (CMP) has quickly become the predominant processor architecture, its c...
The relative ease with which it is possible to build inexpensive, high-performance multicomputers u...
The relative ease with which it is possible to build inexpensive, high-performance multicomputers u...
There is an increasing need for a framework that supports research on portable high-performance para...
As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as paral...
One of the major current challenges in computer science is providing program-ming models and abstrac...
As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as paral...
For a wide variety of applications, both task and data parallelism must be exploited to achieve the ...