NUMA policies and their relation to memory architecture
ASPLOS IV Proceedings of the fourth international conference on Architectural support for programming languages and operating systems
Processor-pool-based scheduling for large-scale NUMA multiprocessors
SIGMETRICS '91 Proceedings of the 1991 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Dynamic and static load scheduling performance on a NUMA shared memory multiprocessor
ICS '91 Proceedings of the 5th international conference on Supercomputing
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
Evaluation of memory system extensions
ISCA '91 Proceedings of the 18th annual international symposium on Computer architecture
Experimental comparison of memory management policies for NUMA multiprocessors
ACM Transactions on Computer Systems (TOCS)
Performance Prediction and Evaluation of Parallel Processing on a NUMA Multiprocessor
IEEE Transactions on Software Engineering
Distributed computing in a NUMP (Non-Uniform Message-Passing) environment
ACM SIGOPS Operating Systems Review
ICS '93 Proceedings of the 7th international conference on Supercomputing
Program Structuring for Effective Parallel Portability
IEEE Transactions on Parallel and Distributed Systems
Micro-pages: increasing DRAM efficiency with locality-aware data placement
Proceedings of the fifteenth edition of ASPLOS on Architectural support for programming languages and operating systems
Handling the problems and opportunities posed by multiple on-chip memory controllers
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
| Hi-index | 0.00 |
Non-uniformity of memory access is an almost inevitable feature of memory architecture in shared memory multiprocessor designs that can scale to large numbers of processors. One implication of NUMA architectures is that the placement and movement of code and data become crucial to performance. As memory architectures become more complex and the nonuniformity becomes less well hidden, systems software must assume a larger role in providing memory management support for the programmer. This paper investigates the role of the operating system. We take an experimental approach to evaluating a wide-range of memory management policies. The target NUMA environment is BBN''s GP-1000 multiprocessor. Extensive local modifications have been made to the memory management subsystem of BBN''s nX operating system to support multiple policy implementations. Policy comparisons are based on the measured performance of real parallel applications. Our results show that there are memory management policies implemented in our system that can improve the performance of programs written using the simpler uniform memory access (UMA) programming model. While achieving the level of performance of a highly tuned NUMA program is still a difficult problem, some examples come close. There appears to be no single policy that can be considered the best over our set of test applications. Investigations into the contributions made by individual policy features toward overall behavior of the workload provide some insight into the design of a set of effective policies.