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This paper summarizes the ideas and key concepts in MISE (Memory Interference-induced Slowdown Estimation), which was published in HPCA 2013 [97], and examines the work's significance and future potential. Applications running concurrently…

Hardware Architecture · Computer Science 2018-05-16 Lavanya Subramanian , Vivek Seshadri , Yoongu Kim , Ben Jaiyen , Onur Mutlu

In a multicore system, applications running on different cores interfere at main memory. This inter-application interference degrades overall system performance and unfairly slows down applications. Prior works have developed…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-04-03 Lavanya Subramanian , Donghyuk Lee , Vivek Seshadri , Harsha Rastogi , Onur Mutlu

The latest trends in high-performance computing systems show an increasing demand on the use of a large scale multicore systems in a efficient way, so that high compute-intensive applications can be executed reasonably well. However, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-02-25 Juliana M. N. Silva , Cristina Boeres , Lúcia M. A. Drummond , Artur A. Pessoa

Shared resource interference is observed by applications as dynamic performance asymmetry. Prior art has developed approaches to reduce the impact of performance asymmetry mainly at the operating system and architectural levels. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-24 Jing Chen , Pirah Noor Soomro , Mustafa Abduljabbar , Madhavan Manivannan , Miquel Pericas

Multi-core architectures can be leveraged to allow independent processes to run in parallel. However, due to resources shared across cores, such as caches, distinct processes may interfere with one another, e.g. affecting execution time.…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-17 Dan Iorga , Tyler Sorensen , Alastair F. Donaldson

Modern Infrastructure-as-a-Service Clouds operate in a competitive environment that caters to any user's requirements for computing resources. The sharing of the various types of resources by diverse applications poses a series of…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-01-28 Evangelos Angelou , Konstantinos Kaffes , Athanasia Asiki , Georgios Goumas , Nectarios Koziris

Heterogeneity has grown in popularity both at the core and server level as a way to improve both performance and energy efficiency. However, despite these benefits, scheduling applications in heterogeneous machines remains challenging.…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-19 Francisco Romero , Christina Delimitrou

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

When multiple processor cores (CPUs) and a GPU integrated together on the same chip share the off-chip DRAM, requests from the GPU can heavily interfere with requests from the CPUs, leading to low system performance and starvation of cores.…

Hardware Architecture · Computer Science 2018-05-01 Rachata Ausavarungnirun , Gabriel H. Loh , Lavanya Subramanian , Kevin Chang , Onur Mutlu

The adoption of high-performance multi-core platforms in avionics and automotive systems introduces significant challenges in ensuring predictable execution, primarily due to shared resource interferences. Many existing approaches study…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-14 Mohamed Amine Khelassi , Felix Suchert , Abderaouf Amalou , Benjamin Lesage , Anika Christmann , Robin Hapka , Jeronimo Castrillon , Mihail Asavoae , Mathieu Jan , Claire Pagetti , Selma Saidi

Storage systems have not kept the same technology improvement rate as computing systems. As applications produce more and more data, I/O becomes the limiting factor for increasing application performance. I/O congestion caused by concurrent…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-03 Hatem Elshazly , Jorge Ejarque , Francesc Lordan , Rosa M. Badia

Many HPC applications suffer from a bottleneck in the shared caches, instruction execution units, I/O or memory bandwidth, even though the remaining resources may be underutilized. It is hard for developers and runtime systems to ensure…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-17 Felippe V. Zacarias , Vinicius Petrucci , Rajiv Nishtala , Paul Carpenter , Daniel Mossé

Advancements in multi-core have created interest among many research groups in finding out ways to harness the true power of processor cores. Recent research suggests that on-board component such as cache memory plays a crucial role in…

Hardware Architecture · Computer Science 2011-11-15 N. Ramasubramanian , Srinivas V. V. , N. Ammasai Gounden

Performance modeling of parallel applications on multicore processors remains a challenge in computational co-design due to multicore processors' complex design. Multicores include complex private and shared memory hierarchies. We present a…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-26 Atanu Barai , Gopinath Chennupati , Nandakishore Santhi , Abdel-Hameed Badawy , Yehia Arafa , Stephan Eidenbenz

Simultaneous multithreading processors improve throughput over single-threaded processors thanks to sharing internal core resources among instructions from distinct threads. However, resource sharing introduces inter-thread interference…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-10-20 Marta Navarro , Josué Feliu , Salvador Petit , María E. Gómez , Julio Sahuquillo

We study scheduling control of parallel processing networks in which some resources need to simultaneously collaborate to perform some activities and some resources multitask. Resource collaboration and multitasking give rise to…

Optimization and Control · Mathematics 2020-12-29 Erhun Özkan

Comprehending the performance bottlenecks at the core of the intricate hardware-software interactions exhibited by highly parallel programs on HPC clusters is crucial. This paper sheds light on the issue of automatically asynchronous MPI…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-06 Ayesha Afzal , Georg Hager , Stefano Markidis , Gerhard Wellein

Performance modeling of parallel applications on multicore computers remains a challenge in computational co-design due to the complex design of multicore processors including private and shared memory hierarchies. We present a Scalable…

One of the primary sources of unpredictability in modern multi-core embedded systems is contention over shared memory resources, such as caches, interconnects, and DRAM. Despite significant achievements in the design and analysis of…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-18 Ankit Agrawal , Renato Mancuso , Rodolfo Pellizzoni , Gerhard Fohler

The aim of parallel computing is to increase an application performance by executing the application on multiple processors. OpenMP is an API that supports multi platform shared memory programming model and shared-memory programs are…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-11-12 Vibha Rajput , Alok Katiyar
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