The voltage/frequency island (VFI) design paradigm is a practical architecture for energy-efficient networks-on-chip (NoC) systems. In VFI-based NoC systems, each island can be operated with different voltage and clock frequency and thus it is important to carefully partition processing elements (PEs) into islands based on their workloads and communications. In this paper, we propose an energy-efficient design scheme that optimizes energy consumption and hardware costs in VFI-based NoC systems. Since on-chip networks take up a substantial portion of system power budget in NoC-based systems, the proposed scheme uses communication-aware VFI partitioning and tile mapping/routing algorithms to minimize the inter-VFI communications. Experimental results show that the proposed design technique can reduce communication energy consumption by 32---51% over existing techniques and total energy consumption by 3---14%.

Flash memory is being rapidly deployed as data storage for embedded devices such as PDAs, MP3 players, mobile phones and digital cameras due to its low electronic power, non-volatile storage, high performance, physical stability and portability. The most prominent characteristic of flash memory is that prewritten data can only be dynamically updated via the time consuming erase operation. Furthermore, every block in flash memory has a limited program/erase cycle. In order to manage these issues, the flash memory controller can be integrated with a software module called the flash translation layer (FTL). This paper surveys the state-of-art FTL algorithms. The FTL algorithms can be classified by the complexity of the algorithms: basic and advance. Furthermore, they can be classified by their corresponding tasks: performance enhancement and durability enhancement. The FTL algorithms corresponding to each classification are further broken down into various schemes depending on the methods they adopt. This paper also provides the information of hardware features of flash memory for FTL programmers.

In High-Level Synthesis, Binary Synthesis is a method for synthesizing compiled applications for which the source code is not available. One of the advantages of FPGAs over processors is the availability of multiple internal and external memory banks. Binary synthesis tools use multiple memory banks if they are able to recover data-structures from the binary. In this work we improve the recovery of data-structures by introducing dynamic memory analysis and combining it with improved static memory analysis. We show that many applications can only be synthesized using dynamic memory analysis. We present two FPGA based architectures for implementing the bound-checking and recovery for the synthesized code. Our experiments show that the proposed technique accelerates the execution of applications which use multiple memory banks concurrently. We demonstrate that many binary applications indeed benefit from this technique.

Multi-processor system-on-chip (MPSoC) simulators are many orders of magnitude slower than the hardware they simulate due to increasing architectural complexity. In this paper, we propose a new application sampling technique to accelerate the simulation of MPSoC design space exploration (DSE). The proposed technique dynamically combines simultaneously executed phases, thus generating a sampling unit. This technique accelerates the simulation by allowing the repeated combinations of parallel phases to be skipped. A complementary technique, called cluster synthesis, is also proposed to improve the simulation acceleration when the number of possible phase combinations increases. Our experimental results show that this technique can accelerate the simulation up to a factor of 800 with a relatively small estimation error.

We present a novel loop transformation technique, particularly well suited for optimizing embedded compilers, where an increase in compilation time is acceptable in exchange for significant performance increase. The transformation technique optimizes loops containing nested conditional blocks. Specifically, the transformation takes advantage of the fact that the Boolean value of the conditional expression, determining the true/false paths, can be statically analyzed using a novel interval analysis technique that can evaluate conditional expressions in the general polynomial form. Results from interval analysis combined with loop dependency information is used to partition the iteration space of the nested loop. In such cases, the loop nest is decomposed such as to eliminate the conditional test, thus substantially reducing the execution time. Our technique completely eliminates the conditional from the loops (unlike previous techniques) thus further facilitating the application of other optimizations and improving the overall speedup. Applying the proposed transformation technique on loop kernels taken from Mediabench, SPEC-2000, mpeg4, qsdpcm and gimp, on average we measured a 2.34X speedup when running on a UltraSPARC processor, a 2.92X speedup when running on an Intel Core Duo processor, a 2.44X speedup when running on a PowerPC G5 processor and a 2.04X speedup when running on an ARM9 processor. Performance improvement, taking the entire application into account, was also promising: for 3 selected applications (mpeg-enc, mpeg-dec and qsdpcm) we measured 15% speedup on best case (5% on average) for the whole application.

Hardware/software (HW/SW) partitioning and scheduling are the crucial steps during HW/SW co-design. It has been shown that they are classical combinatorial optimization problems. Due to the possible sequential or concurrent execution of the tasks, HW/SW partitioning and scheduling has become more difficult to solve optimally. In this paper more efficient heuristic algorithms are proposed for the HW/SW partitioning and scheduling. The proposed algorithm partitions a task graph by iteratively moving the task with highest benefit-to-area ratio in higher priority. The benefit-to-area ratio is updated in each iteration step to cater for the task concurrence. The proposed algorithm for task scheduling executes the task lying in hardware-only critical path in higher priority to enhance the task forecast. A large body of experimental results conclusively shows that the proposed heuristic algorithm for partitioning is superior to the latest efficient combinatorial algorithm (Tabu search) cited in this paper. Moreover, the Tabu search for partitioning has been further improved by utilizing the proposed heuristic solution as its initial solution. In addition, the proposed scheduling algorithm obtains the improvements over the most widely used approaches by up to 10% without large increase in running time.

UML has been widely accepted by the software community for several years. As electronic systems design can no longer be seen as an isolated hardware design activity, UML becomes of significant interest as a unification language for systems description combining both HW and SW components. This article provides a comprehensive view of the UML applied to System-on-Chip (SoC) and hardware-related embedded systems design. The modeling concepts in the UML language are first introduced, including major diagrams for the representation of the behavior and the structure of systems. The principles behind application specific UML customizations (UML profiles) are summarized, and several examples relevant for SoC design are given, such as the SysML (System Modeling Language) and the SoC Profile. Thereafter, various approaches associating UML with existing HW/SW design languages are presented. Beyond language aspects, the article addresses the question of UML-based design flows, and shows how UML can be applied concretely to the development of electronic-based systems. The current situation about tool support constitutes the last focus of the article. In particular, we show how UML tools can be combined with well-known simulation environments, such as MATLAB.