Volume II: Privileged Architecture Privileged Architecture Version 1.10 Document Version 1.10 Warning! This draft specification may change before being accepted as standard by the RISC-V Foundation. While the editors intend future changes to this specification to be forward compatible, it remains possible that implementations made to this draft specification will not conform to the future standard.

/pdf/the-risc-v-instruction-set-manual-30b1gwzcmv.pdf

The RISC-V Instruction Set Manual

Future computing workloads will emphasize an architecture's ability to perform relatively simple calculations on massive quantities of mixed-width data. This paper describes a novel reconfigurable fabric architecture, PipeRench, optimized to accelerate these types of computations. PipeRench enables fast, robust compilers, supports forward compatibility, and virtualizes configurations, thus removing the fixed size constraint present in other fabrics. For the first time we explore how the bit-width of processing elements affects performance and show how the PipeRench architecture has been optimized to balance the needs of the compiler against the realities of silicon. Finally, we demonstrate extreme performance speedup on certain computing kernels (up to 190x versus a modern RISC processor), and analyze how this acceleration translates to application speedup.

/pdf/piperench-a-co-processor-for-streaming-multimedia-2zu0mowwqv.pdf

PipeRench: a co/processor for streaming multimedia acceleration

Trends in VLSI technology scaling demand that future computing devices be narrowly focused to achieve high performance and high efficiency, yet also target the high volumes and low costs of widely applicable general purpose designs. To address these conflicting requirements, we propose a modular reconfigurable architecture called Smart Memories, targeted at computing needs in the 0.1m technology generation. A Smart Memories chip is made up of many processing tiles, each containing local memory, local interconnect, and a processor core. For efficient computation under a wide class of possible applications, the memories, the wires, and the computational model can all be altered to match the applications. To show the applicability of this design, two very different machines at opposite ends of the architectural spectrum, the Imagine stream processor and the Hydra speculative multiprocessor, are mapped onto the Smart Memories computing substrate. Simulations of the mappings show that the Smart Memories architecture can successfully map these architectures with only modest performance degradation.

Smart Memories: a modular reconfigurable architecture

Eight synergistic processor units enable the Cell Broadband Engine's breakthrough performance. The SPU architecture implements a novel, pervasively data-parallel architecture combining scalar and SIMD processing on a wide data path. A large number of SPUs per chip provide high thread-level parallelism. The streamlined architecture provides an efficient multithreaded execution environment for both scalar and SIMD threads and represents a reaffirmation of the RISC principles of combining leading edge architecture and compiler optimizations. These design decisions have enabled the Cell BE to deliver unprecedented supercomputer-class compute power for consumer applications

Synergistic Processing in Cell's Multicore Architecture

Increasing focus on multimedia applications has prompted the addition of multimedia extensions to most existing general purpose microprocessors. This added functionality comes primarily with the addition of short SIMD instructions. Unfortunately, access to these instructions is limited to in-line assembly and library calls. Generally, it has been assumed that vector compilers provide the most promising means of exploiting multimedia instructions. Although vectorization technology is well understood, it is inherently complex and fragile. In addition, it is incapable of locating SIMD-style parallelism within a basic block.In this paper we introduce the concept of Superword Level Parallelism (SLP) ,a novel way of viewing parallelism in multimedia and scientific applications. We believe SLPP is fundamentally different from the loop level parallelism exploited by traditional vector processing, and therefore demands a new method of extracting it. We have developed a simple and robust compiler for detecting SLPP that targets basic blocks rather than loop nests. As with techniques designed to extract ILP, ours is able to exploit parallelism both across loop iterations and within basic blocks. The result is an algorithm that provides excellent performance in several application domains. In our experiments, dynamic instruction counts were reduced by 46%. Speedups ranged from 1.24 to 6.70.

/pdf/exploiting-superword-level-parallelism-with-multimedia-1ihagkottn.pdf

Exploiting superword level parallelism with multimedia instruction sets

There is a clear trend in personal computing toward multimedia-rich applications. These applications will incorporate a wide variety of multimedia technologies, including audio and video compression, 2D image processing, 3D graphics, speech and handwriting recognition, media mining, and narrow/broadband signal processing for communication. In response to this demand, major microprocessor vendors have announced architectural extensions to their general-purpose processors in an effort to improve their multimedia performance. Intel extended IA-32 with MMX and SSE (alias KNI), Sun enhanced Sparc with VIS, Hewlett-Packard added MAX to its PA-RISC architecture, Silicon Graphics extended the MIPS architecture with MDMX, and Digital (now Compaq) added MVI to Alpha. This article describes the most recent, and what we believe to be the most comprehensive, addition to this list: PowerPC's AltiVec, AltiVec speeds not only media processing but also nearly any application in which data parallelism exists, as demonstrated by a cycle-accurate simulation of Motorola's MPC 7400, the heart of Apple G4 systems.

AltiVec extension to PowerPC accelerates media processing

Workloads drive architecture design and will change in the next two decades. For high-performance, general-purpose processors, there is a consensus that multimedia will continue to grow in importance. The authors predict these processors will incorporate more media processing capabilities, eventually bringing about the demise of specialized media processors, except perhaps, in embedded applications. These enhanced general-purpose processor capabilities will arise from multimedia applications that require real-time response, continuous-media data types and significant fine-grained data parallelism.

K. Diefendorff

Papers

AltiVec extension to PowerPC accelerates media processing

How multimedia workloads will change processor design