skip to main content
10.1145/3145617acmconferencesBook PagePublication PagesscConference Proceedingsconference-collections
MCHPC'17: Proceedings of the Workshop on Memory Centric Programming for HPC
ACM2017 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SC '17: The International Conference for High Performance Computing, Networking, Storage and Analysis Denver CO USA November 12 - 17, 2017
ISBN:
978-1-4503-5131-7
Published:
12 November 2017
Sponsors:
SIGHPC, IEEE CS

Bibliometrics
Abstract

No abstract available.

Skip Table Of Content Section
SESSION: Research Papers
short-paper
Principles of Memory-Centric Programming for High Performance Computing

The memory wall challenge -- the growing disparity between CPU speed and memory speed -- has been one of the most critical and long-standing challenges in computing. For high performance computing, programming to achieve efficient execution of parallel ...

research-article
Persistent Memory: The Value to HPC and the Challenges

This paper provides an overview of the expected value of emerging persistent memory technologies to high performance computing (HPC) use cases. These values are somewhat speculative at the time of writing, based on what has been announced by vendors to ...

research-article
Bit Contiguous Memory Allocation for Processing In Memory

Given the recent resurgence of research into processing in or near memory systems, we find an ever increasing need to augment traditional system software tools in order to make efficient use of the PIM hardware abstractions. One such architecture, the ...

research-article
Beyond 16GB: Out-of-Core Stencil Computations

Stencil computations are a key class of applications, widely used in the scientific computing community, and a class that has particularly benefited from performance improvements on architectures with high memory bandwidth. Unfortunately, such ...

short-paper
NUMA Distance for Heterogeneous Memory

Experience with Intel Xeon Phi suggests that NUMA alone is inadequate for assignment of pages to devices in heterogeneous memory systems. We argue that this is because NUMA is based on a single distance metric between all domains (i.e., number of ...

short-paper
Evaluating GPGPU Memory Performance Through the C-AMAT Model

General Purpose Graphics Processing Units (GPGPU) have become a popular platform to accelerate high performance applications. Although they provide exceptional computing power, GPGPU impose significant pressure on the off-chip memory system. Evaluating, ...

Recommendations