PROFET

Author:

Radulovic Milan1,Sánchez Verdejo Rommel1,Carpenter Paul2,Radojković Petar2,Jacob Bruce3,Ayguadé Eduard1

Affiliation:

1. Barcelona Supercomputing Center & Universitat Politècnica de Catalunya, Barcelona, Spain

2. Barcelona Supercomputing Center, Barcelona, Spain

3. University of Maryland, College Park, MD, USA

Abstract

The approaching end of DRAM scaling and expansion of emerging memory technologies is motivating a lot of research in future memory systems. Novel memory systems are typically explored by hardware simulators that are slow and often have a simplified or obsolete abstraction of the CPU. This study presents PROFET, an analytical model that predicts how an application's performance and energy consumption changes when it is executed on different memory systems. The model is based on instrumentation of an application execution on actual hardware, so it already takes into account CPU microarchitectural details such as the data prefetcher and out-of-order engine. PROFET is evaluated on two real platforms: Sandy Bridge-EP E5-2670 and Knights Landing Xeon Phi platforms with various memory configurations. The evaluation results show that PROFET's predictions are accurate, typically with only 2% difference from the values measured on actual hardware. We release the PROFET source code and all input data required for memory system and application profiling. The released package can be seamlessly installed and used on high-end Intel platforms.

Funder

Generalitat de Catalunya

Horizon 2020

Ministerio de Ciencia y Tecnología

U.S. Department of Defense

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Safety, Risk, Reliability and Quality,Computer Science (miscellaneous)

Reference36 articles.

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4. Analytical Processor Performance and Power Modeling using Micro-Architecture Independent Characteristics

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1. Short Reasons for Long Vectors in HPC CPUs: A Study Based on RISC-V;Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis;2023-11-12

2. Energy Efficiency of Opportunistic Refreshing for Gain-Cell Embedded DRAM;IEEE Transactions on Circuits and Systems I: Regular Papers;2023-04

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