In high-performance systems, stencil computations play a crucial role as they appear in a variety of different fields of application, ranging from partial differential equation solving, to computer simulation of particles' interaction, to image processing and computer vision. The computationally intensive nature of those algorithms created the need for solutions to efficiently implement them in order to save both execution time and energy. This, in combination with their regular structure, has justified their widespread study and the proposal of largely different approaches to their optimization. However, most of these works are focused on aggressive compile time optimization, cache locality optimization, and parallelism extraction for the multicore/multiprocessor domain, while fewer works are focused on the exploitation of custom architectures to further exploit the regular structure of Iterative Stencil Loops (ISLs), specifically with the goal of improving power efficiency. This work introduces a methodology to systematically design power-efficient hardware accelerators for the optimal execution of ISL algorithms on Field-programmable Gate Arrays (FPGAs). As part of the methodology, we introduce the notion of Streaming Stencil Time-step (SST), a streaming-based architecture capable of achieving both low resource usage and efficient data reuse thanks to an optimal data buffering strategy, and we introduce a technique called SSTs queuing that is capable of delivering a pseudolinear execution time speedup with constant bandwidth. The methodology has been validated on significant benchmarks on a Virtex-7 FPGA using the Xilinx Vivado suite. Results demonstrate how the efficient usage of the on-chip memory resources realized by an SST allows one to treat problem sizes whose implementation would otherwise not be possible via direct synthesis of the original, unmanipulated code via High-Level Synthesis (HLS). We also show how the SSTs queuing effectively ensures a pseudolinear throughput speedup while consuming constant off-chip bandwidth. CCS Concepts: r Hardware → Hardware-software codesign; Methodologies for EDA; Sequential circuits; r Software and its engineering → Data flow architectures; r Theory of computation → Streaming models; Massively parallel algorithms;
Abstract-Designing applications for heterogeneous systems, like Multiprocessor System-on-Chips (MPSoCs) based on Field Programmable Gate Arrays (FPGAs) is a complex task. In order to exploit all the capabilities of these systems, such as Partial Dynamic Reconfiguration (PDR) and hardware acceleration, the designer still has to develop large parts of the system unassisted, establishing the design choices (i.e., whether to assign a task of the application on a hardware region of the FPGA or a general purpose processor of the SoC) mostly on his/her experience.In this paper we present a Mixed-Integer Linear Programming (MILP) formulation for mapping and scheduling of applications on heterogeneous and reconfigurable devices taking into account PDR, module reuse and configuration prefetching. Starting from a target architecture and a description of the application in terms of tasks and data dependencies, the proposed formulation allows the designer to optimize a linear combination of different metrics such as execution time, peak power and energy consumption.
Constraining the temperature of computing systems has become a dominant aspect in the design of integrated circuits. The supply voltage decrease has lost its pace even though the feature size is shrinking constantly. This results in an increased number of transistors per unit of area and hence a growing power density. Researchers started investigating dynamic thermal management techniques to address the tradeoff between performance and temperature. Hardware dynamic thermal management can guarantee safety but, at the same time, can negatively affect established service-level agreements. On the other hand, software solutions rely on hardware for safety but does not indiscriminately trade-off performance for temperature.We propose ThermOS, an extension for commodity operating systems that harnesses formal feedback control and idle cycle injection to decrease thermal emergencies while showing better efficiency than commodity and cutting edge techniques.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.