Systematic architecture exploration from vast solution space is a complex problem in embedded system design. It is very difficult to explore a best architecture fast and accurately because accurate evaluation usually consumes significant amount of time for point in the solution space. In this paper, we propose fast and systematic architecture exploration method for address generation unit (AGU) based on a coarse grained reconfigurable architecture model. First we prove that a set of Pareto solutions of cycle vs energy becomes a subset of Pareto solutions of cycle vs area under some practical assumptions. In addition we propose ldquoOptimistic cycle (OC)rdquo metric to find out promising solutions from vast solution space. Based on this metric we also propose a fast architecture exploration algorithm which only applies mapping to promising architectures. Using the proposed systematic architecture exploration method, we show that we can obtain almost the same trade-off points as the exhaustive search method and also that our method is about 164 times faster than exhaustive search.

Modern handheld embedded systems operate under stringent power and real-time constraints. These systems run highly data-dominated applications from multimedia and wireless domains. Most of these applications spend significant amount of execution time in nested-loops. In order to reduce the loop control overhead several loop controller architectures have been proposed in the past. In this paper we present a generic architecture and a compiler technique to significantly reduce the energy overhead related to execution of loop control instructions. The compiler technique not only maps the innermost loops but also maps the outer loops on to the loop controller architecture. Furthermore, we also reduce the number of division operations using induction variable analysis to improve energy efficiency. We show that by utilizing the proposed technique, it is possible to reduce the energy consumption of the branch operations using these loop controller architectures by 25% on average with no performance loss.

Reduced energy consumption is one of the most important design goals for embedded application domains like wireless communication, multimedia and biomedical applications. The instruction memory hierarchy has been proven to be one of the most power hungry parts of the system. This paper introduces an architectural enhancement for the instruction memory to reduce energy consumption and improve performance. The proposed distributed instruction memory organization requires minimal hardware overhead and supports the execution of multiple incompatible loops in parallel in a uni-processor system. We present different methods to implement the loop controller architecture, compare them, and show that distributing the instruction memory helps to reduce the interconnect cost as well. This architecture enhancement can reduce the energy consumed in the instruction memory hierarchy by 59% and improve the performance by 22% compared to hardware based enhanced SMT based architectures.

Modern mobile devices need to be extremely energy efficient. Due to the growing complexity of these devices, energy-aware design exploration has become increasingly important. Current exploration tools often do not support energy estimation, or require the design to be very detailed before estimation is possible. It is important to get early feedback on both performance and energy consumption during all phases of the design and at higher abstraction levels. This article presents a unified optimization and exploration framework to explore source-level transformation to processor architecture design space. The proposed retargetable compiler and simulator framework can map applications to a range of processors and memory configurations, simulate, and report detailed performance and energy estimates. An accurate and consistent energy modeling approach is introduced which can estimate the energy consumption of processor and memories at a component level, which can help to guide the design process. Fast energy-aware architecture exploration is illustrated by modeling both state-of-the-art processors as well as other architectures. Various design trade-offs are also illustrated on different academic as well as industrial benchmarks from both the wireless communication and multimedia domain. We also illustrate a design space exploration on different applications and show that there is large trade-off space between application performance, energy consumption, and area. We show that the proposed framework is consistent, accurate, and covers a large design space including various novel low-power extensions in a unified framework.

Modern portable embedded devices require processors that can provide sufficient performance for demanding multimedia and wireless applications. At the same time they have to be flexible to support a wide range of products and extremely energy efficient to provide a long battery life. Coarse grained reconfigurable architectures (CGRAs) potentially meet these constraints by providing a mix of flexible computational resources and large amounts of programmable interconnect. The vast design space of CGRAs complicates the development of optimized processors. Most effort has been spent on improving the performance. However, the energy cost of the programmable interconnect is becoming more expensive and this cost can no longer be neglected. In this work we present an energy- and performance-aware exploration for the interconnect of a CGRA and show that important tradeoffs can be made for those metrics. This will enable designers to develop more efficient architectures, tuned to a targeted application domain.

To achieve energy reduction for instruction memory access in VLIW ASIPs, operation shuffling technique has been proposed. The shuffling technique changes assignment of an operation to different slot so that L0 cluster configuration can be improved. The published technique, however, moves operations within a cycle, not between cycles. As a result, the potential gain of energy reduction was limited. This paper proposes a shuffling technique that also moves operations between cycles as well as within a cycle. The experimental results show that the proposed method achieves more efficient energy than the best known shuffling method by up to 15.3% in the best case.

In current embedded systems processors, multi-ported register files are one of the most power hungry parts of the processor, even when they are clustered. This paper presents a novel register file architecture, which has single ported cells and asymmetric interfaces to the memory and to the datapath. Several realistic kernels from the TI DSP benchmark and from software defined radio (SDR) are mapped on the architecture. A complete physical design of the architecture is done in TSMC 90nm technology. The novel architecture presented is shown to obtain energy gains of up to 10times with respect to conventional multi-ported register file over the different benchmarks

Clustering L0 buffers is effective for energy reduction in the instruction memory hierarchy of embedded VLIW processors. However, the efficiency of the clustering depends on the schedule of the target application. Especially in heterogeneous or data clustered VLIW processors, determining energy efficient scheduling is more constraining. This article proposes a realistic technique supported by a tool flow to explore operation shuffling for improving generation of L0 clusters. The tool flow explores assignment of operations for each cycle and generates various schedules. This approach makes it possible to reduce energy consumption for various processor architectures. However, the computational complexity is large because of the huge exploration space. Therefore, some heuristics are also developed, which reduce the size of the exploration space while the solution quality remains reasonable. Furthermore, we also propose a technique to support VLIW processors with multiple data clusters, which is essential to apply the methodology to real world processors. The experimental results indicate potential gains of up to 27.6% in energy in L0 buffers, through operation shuffling for heterogeneous processor architectures as well as a homogeneous architecture. Furthermore, the proposed heuristics drastically reduce the exploration search space by about 90%, while the results are comparable to full search, with average differences of less than 1%. The experimental results indicate that energy efficiency can be improved in most of the media benchmarks by the proposed methodology, where the average gain is around 10% in comparison with generating clusters without operation shuffling.

Reduced energy consumption is one of the most important design goals for embedded application domains like wireless, multimedia and biomedical. Instruction memory hierarchy has been proven to be one of the most power hungry parts of the system. This paper introduces an architectural enhancement for the instruction memory to reduce energy and improve performance. The proposed distributed instruction memory organization requires minimal hardware overhead and allows execution of multiple loops in parallel in a uni-processor system. This architecture enhancement can reduce the energy consumed in the instruction and data memory hierarchy by 70.01 % and improve the performance by 32.89% compared to enhanced SMT based architectures

Users expect future handheld devices to provide extended multimedia functionality and have long battery life. This type of application imposes heavy constraints on performance and power consumption and forces designers to optimize all parts of their platform. Evaluating the overall platform power breakdown is therefore critical to determine where to spend the efforts on power optimization. Surprisingly, few studies exist on that topic and decisions generally rely on common belief. We have realized a complete power breakdown for a realistic platform to identify the major power bottlenecks. This paper presents this power assessment of a realistic heterogeneous network on chip platform including processors, network and data/instruction memory hierarchy, running a video processing chain from camera to display. Our power breakdown identifies the main bottlenecks in the memory hierarchy and the foreground memory, and shows that global interconnect is not that critical for a well-optimized application mapping.

Current loop buffer organizations for very large instruction word processors are essentially centralized. As a consequence, they are energy inefficient and their scalability is limited. To alleviate this problem, we propose a clustered loop buffer organization, where the loop buffers are partitioned and functional units are logically grouped to form clusters, along with two schemes for buffer control, which regulate the activity in each cluster. Furthermore, we propose a design-time scheme to generate clusters by analyzing an application profile and grouping closely related functional units. The simulation results indicate that the energy consumed in the clustered loop buffers is, on average, 63 percent lower than the energy consumed in an uncompressed centralized loop buffer scheme, 35 percent lower than a centralized compressed loop buffer scheme, and 22 percent lower than a randomly clustered loop buffer scheme.

Users expect future handheld devices to provide extended multimedia functionality and have long battery life. This type of application imposes heavy constraints on both (realtime) performance and energy consumption and forces designers to optimise all parts of their platform. In this experiment we focus on the different processor core design options for embedded platforms, including the effect of instruction memory hierarchy on the energy consumption. The results show that significant improvements for energy efficiency and/or performance over currently used RISC or VLIW processors can be achieved. We conclude, based on concrete data for a realistic application, that different styles, including both configurable hardware and instruction set processors, find their way into heterogeneous platforms and designers need to be aware of the trade-offs. Secondly, we show for the same application task that a heavily optimised instruction/configuration memory hierarchy can significantly reduce the energy consumption of this part, so it forms a crucial part of every energy aware design.