Compiler optimization and ordering effects on VLIW code compression

Code size has always been an important issue for all embedded applications as well as larger systems. Code compression techniques have been devised as a way of battling bloated code; however, the impact of VLIW compiler methods and outputs on these compression schemes has not been thoroughly investigated. This paper describes the application of single- and multipleinstruction dictionary methods for code compression to decrease overall code size for the TI TMS320C6xxx DSP family. The compression scheme is applied to benchmarks taken from the Mediabench benchmark suite built with differing compiler optimization parameters. In the single instruction encoding scheme, it was found that compression ratios were not a useful indicator of the best overall code size – the best results (smallest overall code size) were obtained when the compression scheme was applied to sizeoptimized code. In the multiple instruction encoding scheme, changing parallel instruction order was found to only slightly improve compression in unoptimized code and does not affect the code compression when it is applied to builds already optimized for size

Design and Simulation of High Performance Parallel Architectures Using the ISAC Language

Most of modern embedded systems for multimediaand network applications are based on parallel data streamprocessing. The data processing can be done using very longinstruction word processors (VLIW), or using more than onehigh performance application-specific instruction set processor(ASIPs), or even by their combination on single chip.Design and testing of these complex systems is time-consumingand iterative process. Architecture description languages (ADLs)are one of the most effective solutions for single processor design.However, support for description of parallel architectures andmulti-processor systems is very low or completely missing innowadays ADLs. This article presents utilization of newextensions for existing architecture description language ISAC.These extensions are used for easy and fast prototyping andtesting of parallel based systems and processors

KAVUAKA: a low-power application-specific processor architecture for digital hearing aids

The power consumption of digital hearing aids is very restricted due to their small physical size and the available hardware resources for signal processing are limited. However, there is a demand for more processing performance to make future hearing aids more useful and smarter. Future hearing aids should be able to detect, localize, and recognize target speakers in complex acoustic environments to further improve the speech intelligibility of the individual hearing aid user. Computationally intensive algorithms are required for this task. To maintain acceptable battery life, the hearing aid processing architecture must be highly optimized for extremely low-power consumption and high processing performance.The integration of application-specific instruction-set processors (ASIPs) into hearing aids enables a wide range of architectural customizations to meet the stringent power consumption and performance requirements. In this thesis, the application-specific hearing aid processor KAVUAKA is presented, which is customized and optimized with state-of-the-art hearing aid algorithms such as speaker localization, noise reduction, beamforming algorithms, and speech recognition. Specialized and application-specific instructions are designed and added to the baseline instruction set architecture (ISA). Among the major contributions are a multiply-accumulate (MAC) unit for real- and complex-valued numbers, architectures for power reduction during register accesses, co-processors and a low-latency audio interface. With the proposed MAC architecture, the KAVUAKA processor requires 16 % less cycles for the computation of a 128-point fast Fourier transform (FFT) compared to related programmable digital signal processors. The power consumption during register file accesses is decreased by 6 %to 17 % with isolation and by-pass techniques. The hardware-induced audio latency is 34 %lower compared to related audio interfaces for frame size of 64 samples.The final hearing aid system-on-chip (SoC) with four KAVUAKA processor cores and ten co-processors is integrated as an application-specific integrated circuit (ASIC) using a 40 nm low-power technology. The die size is 3.6 mm2. Each of the processors and co-processors contains individual customizations and hardware features with a varying datapath width between 24-bit to 64-bit. The core area of the 64-bit processor configuration is 0.134 mm2. The processors are organized in two clusters that share memory, an audio interface, co-processors and serial interfaces. The average power consumption at a clock speed of 10 MHz is 2.4 mW for SoC and 0.6 mW for the 64-bit processor.Case studies with four reference hearing aid algorithms are used to present and evaluate the proposed hardware architectures and optimizations. The program code for each processor and co-processor is generated and optimized with evolutionary algorithms for operation merging,instruction scheduling and register allocation. The KAVUAKA processor architecture is com-pared to related processor architectures in terms of processing performance, average power consumption, and silicon area requirements

Trends in hardware architecture for mobile devices

In the last ten years, two main factors have fueled the steady growth in sales of mobile computing and communication devices: a) the reduction of the footprint of the devices themselves, such as cellular handsets and small computers; and b) the success in developing low-power hardware which allows the devices to operate autonomously for hours or even days. In this review, I show that the first generation of mobile devices was DSP centric – that is, its architecture was based in fast processing of digitized signals using low- power, yet numerically powerful DSPs. However, the next generation of mobile devices will be built around DSPs and low power microprocessor cores for general processing applications. Mobile devices will become data-centric. The main challenge for designers of such hybrid architectures is to increase the computational performance of the computing unit, while keeping power constant, or even reducing it. This report shows that low-power mobile hardware architectures design goes hand in hand with advances in compiling techniques. We look at the synergy between hardware and software, and show that a good balance between both can lead to innovative lowpower processor architectures

Siirtoliipaisuarkkitehtuurin muuttuvanmittaisten käskyjen pakkaus

The Static Random-Access Memory (SRAM) modules used for embedded microprocessor devices consume a large portion of the whole system’s power. The memory module consumes static power on keeping awake and dynamic power on memory accesses. The power dissipation of the instruction memory can be limited by using code compression methods, which reduce the memory size. The compression may require the use of variable length instruction formats in the processor. The power-efficient design of variable length instruction fetch and decode units is challenging for static multiple-issue processors, because such architectures have simple hardware to begin with, as they aim for very low power consumption on embedded platforms. The power saved by using these compression approaches, which necessitate more complex logic, is easily lost on inefficient processor design. This thesis proposes an implementation for instruction template-based compression, its decompression and two instruction fetch design alternatives for variable length instruction encoding on Transport Triggered Architecture (TTA), a static multiple-issue exposed data path architecture. Both of the new fetch and decode units are integrated into the TTA-based Co-design Environment (TCE), which is a toolset for rapid designing and prototyping of processors based on TTA. The hardware description of the fetch units is verified on a register transfer level and benchmarked using the CHStone test suite. Furthermore, the fetch units are synthesized on a 40 nm standard cell Application Specific Integrated Circuit (ASIC) technology library for area, performance and power consumption measurements. The power cost of the variable length instruction support is compared to the power savings from memory reduction, which is evaluated using HP Labs’ CACTI tool. The compression approach reaches an average program size reduction of 44% at best with a set of test programs, and the total power consumption of the system is reduced. The thesis shows that the proposed variable length fetch designs are sufficiently low-power oriented for TTA processors to benefit from the code compression

Exploring Processor and Memory Architectures for Multimedia

Multimedia has become one of the cornerstones of our 21st century society and, when combined with mobility, has enabled a tremendous evolution of our society. However, joining these two concepts introduces many technical challenges. These range from having sufficient performance for handling multimedia content to having the battery stamina for acceptable mobile usage. When taking a projection of where we are heading, we see these issues becoming ever more challenging by increased mobility as well as advancements in multimedia content, such as introduction of stereoscopic 3D and augmented reality. The increased performance needs for handling multimedia come not only from an ongoing step-up in resolution going from QVGA (320x240) to Full HD (1920x1080) a 27x increase in less than half a decade. On top of this, there is also codec evolution (MPEG-2 to H.264 AVC) that adds to the computational load increase. To meet these performance challenges there has been processing and memory architecture advances (SIMD, out-of-order superscalarity, multicore processing and heterogeneous multilevel memories) in the mobile domain, in conjunction with ever increasing operating frequencies (200MHz to 2GHz) and on-chip memory sizes (128KB to 2-3MB). At the same time there is an increase in requirements for mobility, placing higher demands on battery-powered systems despite the steady increase in battery capacity (500 to 2000mAh). This leaves negative net result in-terms of battery capacity versus performance advances. In order to make optimal use of these architectural advances and to meet the power limitations in mobile systems, there is a need for taking an overall approach on how to best utilize these systems. The right trade-off between performance and power is crucial. On top of these constraints, the flexibility aspects of the system need to be addressed. All this makes it very important to reach the right architectural balance in the system. The first goal for this thesis is to examine multimedia applications and propose a flexible solution that can meet the architectural requirements in a mobile system. Secondly, propose an automated methodology of optimally mapping multimedia data and instructions to a heterogeneous multilevel memory subsystem. The proposed methodology uses constraint programming for solving a multidimensional optimization problem. Results from this work indicate that using today’s most advanced mobile processor technology together with a multi-level heterogeneous on-chip memory subsystem can meet the performance requirements for handling multimedia. By utilizing the automated optimal memory mapping method presented in this thesis lower total power consumption can be achieved, whilst performance for multimedia applications is improved, by employing enhanced memory management. This is achieved through reduced external accesses and better reuse of memory objects. This automatic method shows high accuracy, up to 90%, for predicting multimedia memory accesses for a given architecture