Run-time optimization of a dynamically reconfigurable embedded system through performance prediction

Author(s):  
Giovanni Mariani ◽  
Vlad-Mihai Sima ◽  
Gianluca Palermo ◽  
Vittorio Zaccaria ◽  
Giacomo Marchiori ◽  
...  
10.28945/3391 ◽  
2009 ◽  
Author(s):  
Moshe Pelleh

In our world, where most systems become embedded systems, the approach of designing embedded systems is still frequently similar to the approach of designing organic systems (or not embedded systems). An organic system, like a personal computer or a work station, must be able to run any task submitted to it at any time (with certain constrains depending on the machine). Consequently, it must have a sophisticated general purpose Operating System (OS) to schedule, dispatch, maintain and monitor the tasks and assist them in special cases (particularly communication and synchronization between them and with external devices). These OSs require an overhead on the memory, on the cache and on the run time. Moreover, generally they are task oriented rather than machine oriented; therefore the processor's throughput is penalized. On the other hand, an embedded system, like an Anti-lock Braking System (ABS), executes always the same software application. Frequently it is a small or medium size system, or made up of several such systems. Many small or medium size embedded systems, with limited number of tasks, can be scheduled by our proposed hardware architecture, based on the Motorola 500MHz MPC7410 processor, enhancing its throughput and avoiding the software OS overhead, complexity, maintenance and price. Encouraged by our experimental results, we shall develop a compiler to assist our method. In the meantime we will present here our proposal and the experimental results.


Author(s):  
Naim Harb ◽  
Smail Niar ◽  
Mazen A. R. Saghir

Embedded system designers are increasingly relying on Field Programmable Gate Arrays (FPGAs) as target design platforms. Today's FPGAs provide high levels of logic density and rich sets of embedded hardware components. They are also inherently flexible and can be easily and quickly modified to meet changing applications or system requirements. On the other hand, FPGAs are generally slower and consume more power than Application-Specific Integrated Circuits (ASICs). However, advances in FPGA architectures, such as Dynamic Partial Reconfiguration (DPR), are helping bridge this gap. DPR enables a portion of an FPGA device to be reconfigured while the device is still operating. This chapter explores the advantage of using the DPR feature in an automotive system. The authors implement a Driver Assistant System (DAS) based on a Multiple Target Tracking (MTT) algorithm as the automotive base system. They show how the DAS architecture can be adjusted dynamically to different scenario situations to provide interesting functionalities to the driver.


1996 ◽  
Vol 06 (01) ◽  
pp. 173-184 ◽  
Author(s):  
WESLEY K. KAPLOW ◽  
BOLESLAW K. SZYMANSKI

We present a novel, compile-time method for determining the cache performance of the loop nests in a program. The cache hit-rates are produced by applying the reference string, determined during compilation, to an architecturally parameterized cache simulator. We also describe a heuristic that uses this method for compile-time optimization of loop ranges in iteration-space blocking. The results of the loop program optimizations are presented for different parallel program benchmarks and various processor architectures, such as IBM SP1 RS/6000, the SuperSPARC, and the Intel 1860.


2020 ◽  
Vol 10 (3) ◽  
pp. 25
Author(s):  
Ali Aalsaud ◽  
Fei Xia ◽  
Ashur Rafiev ◽  
Rishad Shafik ◽  
Alexander Romanovsky ◽  
...  

Contemporary embedded systems may execute multiple applications, potentially concurrently on heterogeneous platforms, with different system workloads (CPU- or memory-intensive or both) leading to different power signatures. This makes finding the most energy-efficient system configuration for each type of workload scenario extremely challenging. This paper proposes a novel run-time optimization approach aiming for maximum power normalized performance under such circumstances. Based on experimenting with PARSEC applications on an Odroid XU-3 and Intel Core i7 platforms, we model power normalized performance (in terms of instruction per second (IPS)/Watt) through multivariate linear regression (MLR). We derive run-time control methods to exploit the models in different ways, trading off optimization results with control overheads. We demonstrate low-cost and low-complexity run-time algorithms that continuously adapt system configuration to improve the IPS/Watt by up to 139% compared to existing approaches.


Author(s):  
Liuqing Li ◽  
Xin Wang ◽  
Xiansen Meng ◽  
Zhiyong Feng
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