AntSM: Efficient Debugging for Shared Memory Parallel Programs

2014 ◽  
pp. 202-216
Author(s):  
Jae-Woo Lee ◽  
Samuel P. Midkiff
Keyword(s):  
Shared Memory ◽  
Parallel Programs

Shared-Memory Parallel Programs

1995 ◽  
pp. 41-85
Author(s):  
Daniel E. Lenoski ◽  
Wolf-Dietrich Weber
Keyword(s):  
Shared Memory ◽  
Parallel Programs

PARALLEL BUDDY MEMORY MANAGEMENT

1992 ◽  
Vol 02 (04) ◽  
pp. 391-398 ◽  
Author(s):  
THEODORE JOHNSON ◽  
TIMOTHY A. DAVIS
Keyword(s):  
Shared Memory ◽  
Memory Management ◽  
Sparse Matrix ◽  
Parallel Programs ◽  
Memory Allocation ◽  
Multiprocessor Systems ◽  
Matrix Algorithm ◽  
Buddy System ◽  
Shared Memory Multiprocessor ◽  
Dynamic Storage

Shared memory multiprocessor systems need efficient dynamic storage allocators, both for system purposes and to support parallel programs. Memory managers are often based on the buddy system, which provides fast allocation and release. Previous parallel buddy memory managers made no attempt to coordinate the allocation, splitting and release of blocks, and as a result needlessly fragment memory. We present a fast and simple parallel buddy memory manager that is also as space efficient as a serial buddy memory manager. We test our algorithms using memory allocation/deallocation traces collected from a parallel sparse matrix algorithm.

scholarly journals Extending OpenMP for NUMA Machines

2000 ◽  
Vol 8 (3) ◽  
pp. 163-181 ◽  
Author(s):  
John Bircsak ◽  
Peter Craig ◽  
RaeLyn Crowell ◽  
Zarka Cvetanovic ◽  
Jonathan Harris ◽  
...  
Keyword(s):  
Shared Memory ◽  
High Performance ◽  
Distributed Memory ◽  
Parallel Programs ◽  
Compiler Optimizations ◽  
High Performance Fortran ◽  
Efficient Code ◽  
Memory Architectures ◽  
Shared Memory Architectures ◽  
Fast Access

This paper describes extensions to OpenMP that implement data placement features needed for NUMA architectures. OpenMP is a collection of compiler directives and library routines used to write portable parallel programs for shared-memory architectures. Writing efficient parallel programs for NUMA architectures, which have characteristics of both shared-memory and distributed-memory architectures, requires that a programmer control the placement of data in memory and the placement of computations that operate on that data. Optimal performance is obtained when computations occur on processors that have fast access to the data needed by those computations. OpenMP -- designed for shared-memory architectures -- does not by itself address these issues. The extensions to OpenMP Fortran presented here have been mainly taken from High Performance Fortran. The paper describes some of the techniques that the Compaq Fortran compiler uses to generate efficient code based on these extensions. It also describes some additional compiler optimizations, and concludes with some preliminary results.

A SCALABLE AND EFFICIENT STORAGE ALLOCATOR ON SHARED-MEMORY MULTIPROCESSORS

2001 ◽  
Vol 11 (02n03) ◽  
pp. 313-325
Author(s):  
VOON-YEE VEE ◽  
WEN-JING HSU
Keyword(s):  
Shared Memory ◽  
Parallel Simulation ◽  
Parallel Programs ◽  
Fixed Size ◽  
Shared Memory Multiprocessors ◽  
Efficient Storage ◽  
Dynamic Storage ◽  
Time Critical ◽  
Lock Contention

An efficient dynamic storage allocator is important for time-critical parallel programs. In this paper, we present a fast and simple parallel allocator for fixed size blocks on shared-memory multiprocessors. We show both theoretically and empirically that the allocator incurs very low lock contention. The allocator is tested with parallel simulation applications with frequent allocation and release requests. The results confirm that our allocator is indeed very efficient.

Sign in / Sign up

Export Citation Format

Share Document