Multicore systems have not only become ubiquitous in the desktop and server worlds, but are also becoming the standard in the embedded space. Multicore offers programmability and flexibility over traditional ASIC solutions. However, many of the advantages of switching to multicore hinge on the assumption that software development is simpler and less costly than hardware development. However, the design and development of correct, high-performance, multi-threaded programs is a difficult challenge for most programmers. Stream programming is one model that has wide applicability in the multimedia, signal processing, and networking domains. Streaming is convenient for developers because it separates the creation of actors, or functions that operate on packets of data, from the flow of data through the system. However, stream compilers are generally ineffective for embedded systems because they do not handle strict resource or timing constraints. Specifically, real-time deadlines and memory size limitations are not handled by conventional stream partitioning and scheduling techniques. This paper introduces the SPIR compiler that orchestrates the execution of streaming applications with strict memory and timing constraints. Software defined radio or SDR is chosen as the application space to illustrate the effectiveness of the compiler for mapping applications onto the IBM Cell platform.

The architectures of system-on-chip (SoC) platforms found in high-end consumer devices are getting more and more complex as designers strive to deliver increasingly compute-intensive applications on near-constant energy budgets. Workloads running on these platforms require the exploitation of heterogeneous parallelism and increasingly irregular memory hierarchies. The conventional approach to programming such hardware is very lowlevel but this yields software which is intimately and inseparably tied to the details of the platform it was originally designed for, limiting the software's portability, and, ultimately, the architectural choices available to designers of future platform generations. The key insight of this paper is that many of the problems experienced in mapping applications onto SoC platforms come not from deciding how to map a program onto the hardware but from the need to restructure the program and the number of interdependencies introduced in the process of implementing those decisions. We tackle this complexity with a set of language extensions which allows the programmer to introduce pipeline parallelism into sequential programs, manage distributed memories, and express the desired mapping of tasks to resources. The compiler takes care of the complex, error-prone details required to implement that mapping. We demonstrate the effectiveness of SoC-C and its compiler with a "software defined radio" example (the PHY layer of a Digital Video Broadcast receiver) achieving a 3.4x speedup on 4 cores.

Previous studies have shown that wireless DSP algorithms exhibit high levels of data level parallelism (DLP). Commercial and research work in the field of software defined radio (SDR) has produced designs utilizing single-instruction multiple-data (SIMD) execution units to exploit this high level of parallelism. These designs have been able to deliver the efficiency and computational power needed to process 3G wireless technologies. Though efficient 3G processing has been achieved, next generation 4G SDR technology requires 10–1000x more computational performance but limits the power budget increase to 2–5x. In this paper, we present a breakdown of 4G and analyze the scalability of SIMD to see if it can help to meet the 4G requirement. We take a proposed SDR architecture, SODA, and modify it for different widths in order to calculate its efficiency. We consider the trade-offs with respect to computation and energy efficiency.

With the multitude of existing and upcoming wireless standards, it is becoming increasingly difficult for hardware-only baseband processing solutions to adapt to the rapidly changing wireless communication landscape. Software defined radio (SDR) promises to deliver a cost effective and flexible solution by implementing a wide variety of wireless protocols in software. In previous work, a fully programmable multicore architecture, SODA, was proposed that was able to meet the real-time requirements of 3G wireless protocols. SODA consists of one ARM control processor and four wide single instruction multiple data (SIMD) processing elements. Each processing element consists of a scalar and a wide 512-bit 32-lane SIMD datapath. A commercial prototype based on the SODA architecture, Ardbeg (named after a brand of Scotch whisky), has been developed. In this paper, we present the architectural evolution of going from a research design to a commercial prototype, including the goals, tradeoffs, and final design choices. Ardbegpsilas redesign process can be grouped into the following three major areas: optimizing the wide SIMD datapath, providing long instruction word (LIW) support for SIMD operations, and adding application-specific hardware accelerators. Because SODA was originally designed with 180 nm technology, the wide SIMD datapath is re-optimized in Ardbeg for 90 nm technology. This includes re-evaluating the most efficient SIMD width, designing a wider SIMD shuffle network, and implementing faster SIMD arithmetic units. Ardbeg also provides modest LIW support by allowing two SIMD operations to issue in the same cycle. This LIW execution supports SDR algorithmspsila most common parallel SIMD execution patterns with minimal hardware overhead. A viable commercial SDR solution must be competitive with existing ASIC solutions. Therefore, algorithm-specific hardware is added for performance bottleneck algorithms while still maintaining enough flexibility to support multiple wireless protocols. The combination of these architectural improvements allows Ardbeg to achieve 1.5-7x speedup over SODA across multiple wireless algorithms while consuming less power.

Software Defined Radio (SDR) is an emerging embedded domain where the physical layer of wireless protocols is implemented in software rather than the traditional application specific hardware. The operation throughput requirements of current third-generation (3G) wireless protocols are an order of magnitude higher than the capabilities of modern DSP processors. Due to this steep performance requirement, heterogeneous multiprocessor system-on-chip designs have been proposed to support SDR. Given the difficulty in compiling traditional digital signal processors, these new multiprocessor architectures provide even greater challenges for the programmers and compilers. In this paper, we utilize a hierarchical dataflow programming model, referred to as SPIR, that is designed for modeling SDR applications. We then present a coarse-grained data ow compilation strategy that assigns a SDR protocol's DSP kernels onto multiple processors, allocates memory buffers, and determines an execution schedule that meets a prescribed throughput. Unlike traditional approaches, coarse-grained compilation exploits task-level parallelism by scheduling concurrent DSP kernels instead of instructions. Because of the streaming nature of SDR protocols, we adapted an existing instruction-level software pipelining technique, modulo scheduling, for coarse-grained compilation. Our compilation methodology is able to generate parallel code that achieves near linear speedup on a SDR multiprocessor system.

The physical layer of most wireless protocols is traditionally implemented in custom hardware to satisfy the heavy computational requirements while keeping power consumption to a minimum. These implementations are time consuming to design and difficult to verify. A programmable hardware platform capable of supporting software implementations of the physical layer, or software defined radio, has a number of advantages. These include support for multiple protocols, faster time-to-market, higher chip volumes, and support for late implementation changes. The challenge is to achieve this without sacrificing power. In this paper, we present a design study for a fully programmable architecture, SODA, that supports software defined radio a high-end signal processing application. Our design achieves high performance, energy efficiency, and programmability through a combination of features that include single-instruction multiple- data (SIMD) parallelism, and hardware optimized for 16bit computations. The basic processing element is an asymmetric processor consisting of a scalar and SIMD pipeline, and a set of distributed scratchpad memories that are fully managed in software. Results show that a four processor design is capable of meeting the throughput requirements of theW-CDMA and 802.11a protocols, while operating within the strict power constraints of a mobile terminal.