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Operating systems have historically had to manage only a single type of memory device. The imminent availability of heterogeneous memory devices based on emerging memory technologies confronts the classic single memory model and opens a new…

A processor's memory hierarchy has a major impact on the performance of running code. However, computing platforms, where the actual hardware characteristics are hidden from both the end user and the tools that mediate execution, such as a…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-10 Keith Cooper , Xiaoran Xu

Modern prefetchers identify memory access patterns in order to predict future accesses. However, many applications exhibit irregular access patterns that do not manifest spatio-temporal locality in the memory address space. Such…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-14 Leeor Peled , Uri Weiser , Yoav Etsion

Recent trends in business and technology (e.g., machine learning, social network analysis) benefit from storing and processing growing amounts of graph-structured data in databases and data science platforms. FPGAs as accelerators for graph…

Databases · Computer Science 2021-02-09 Jonas Dann , Daniel Ritter , Holger Fröning

ESBMC implements many state-of-the-art techniques for model checking. We report on new and improved features that allow us to obtain verification results for previously unsupported programs and properties. ESBMC employs a new static…

Optimizing scientific applications to take full advan-tage of modern memory subsystems is a continual challenge forapplication and compiler developers. Factors beyond working setsize affect performance. A benchmark framework that…

Performance · Computer Science 2018-12-20 Mahesh Lakshminarasimhan , Catherine Olschanowsky

Memory disaggregation has recently been adopted in data centers to improve resource utilization, motivated by cost and sustainability. Recent studies on large-scale HPC facilities have also highlighted memory underutilization. A promising…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-30 Jacob Wahlgren , Gabin Schieffer , Maya Gokhale , Ivy Peng

The ability to understand how a scientific application is executed on a large HPC system is of great importance in allocating resources within the HPC data center. In this paper, we describe how we used system performance data to identify:…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-15 David Brayford , Christoph Bernau , Wolfram Hesse , Carla Guillen

High-end ARM processors are emerging in data centers and HPC systems, posing as a strong contender to x86 machines. Memory-centric profiling is an important approach for dissecting an application's bottlenecks on memory access and guiding…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-03 Samuel Miksits , Ruimin Shi , Maya Gokhale , Jacob Wahlgren , Gabin Schieffer , Ivy Peng

Static performance estimation is essential during compile-time analysis, yet traditional runtime-based methods are costly and platform-dependent. We investigate mems, the number of memory accesses, as a static and architecture-independent…

Software Engineering · Computer Science 2025-05-13 Liwei Zhang , Baoquan Cui , Xutong Ma , Jian Zhang

Accurate performance projection of large-scale benchmarks is essential for CPU architects to evaluate and optimize future processor designs. SimPoint sampling, which uses Basic Block Vectors (BBVs), is a widely adopted technique to reduce…

Hardware Architecture · Computer Science 2025-06-04 Sriyash Caculo , Mahesh Madhav , Jeff Baxter

Memory disaggregation addresses memory imbalance in a cluster by decoupling CPU and memory allocations of applications while also increasing the effective memory capacity for (memory-intensive) applications beyond the local memory limit…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-07 Anil Yelam

Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-19 Stefano Corda , Gagandeep Singh , Ahsan Javed Awan , Roel Jordans , Henk Corporaal

Next-generation supercomputers will feature more hierarchical and heterogeneous memory systems with different memory technologies working side-by-side. A critical question is whether at large scale existing HPC applications and emerging…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-04-27 Ivy Bo Peng , Stefano Markidis , Erwin Laure , Gokcen Kestor , Roberto Gioiosa

Although High Performance Computing (HPC) users understand basic resource requirements such as the number of CPUs and memory limits, internal infrastructural utilization data is exclusively leveraged by cluster operators, who use it to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-19 Abel Souza , Kristiaan Pelckmans , Johan Tordsson

The continued growth of the computational capability of throughput processors has made throughput processors the platform of choice for a wide variety of high performance computing applications. Graphics Processing Units (GPUs) are a prime…

Hardware Architecture · Computer Science 2018-05-01 Rachata Ausavarungnirun

Memory-centric computing aims to enable computation capability in and near all places where data is generated and stored. As such, it can greatly reduce the large negative performance and energy impact of data access and data movement, by…

Hardware Architecture · Computer Science 2023-09-15 Onur Mutlu

Today, very large amounts of data are produced and stored in all branches of society including science. Mining these data meaningfully has become a considerable challenge and is of the broadest possible interest. The size, both in numbers…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-11 Andreas Vitalis

This paper describes a new benchmark tool, Spatter, for assessing memory system architectures in the context of a specific category of indexed accesses known as gather and scatter. These types of operations are increasingly used to express…

Performance · Computer Science 2020-07-09 Patrick Lavin , Jeffrey Young , Jason Riedy , Richard Vuduc , Aaron Vose , Dan Ernst

Modern memory hierarchies work well with applications that have good spatial locality. Evolving (dynamic) graphs are important applications widely used to model graphs and networks with edge and vertex changes. They exhibit irregular memory…

Hardware Architecture · Computer Science 2024-06-21 Abhishek Singh , Christian Schulte , Xiaochen Guo
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