Dr. Lenoski and Dr. Weber have experience with leading-edge research and practical issues involved in implementing large-scale parallel systems. They were key contributors to the architecture and design of the DASH multiprocessor. Currently, they are involved with commercializing scalable shared-memory technology.
The workshop on Scalable Shared Memory Multiprocessors took place on May 26 and 27 1990 at the Stouffer Madison Hotel in Seattle, Washington as a prelude to the 1990 International Symposium on Computer Architecture. About 100 participants listened for two days to the presentations of 22 invited The motivation for this workshop was to speakers, from academia and industry. promote the free exchange of ideas among researchers working on shared-memory multiprocessor architectures. There was ample opportunity to argue with speakers, and certainly participants did not refrain a bit from doing so. Clearly, the problem of scalability in shared-memory multiprocessors is still a wide-open question. We were even unable to agree on a definition of "scalability". Authors had more than six months to prepare their manuscript, and therefore the papers included in this proceedings are refinements of the speakers' presentations, based on the criticisms received at the workshop. As a result, 17 authors contributed to these proceedings. We wish to thank them for their diligence and care. The contributions in these proceedings can be partitioned into four categories 1. Access Order and Synchronization 2. Performance 3. Cache Protocols and Architectures 4. Distributed Shared Memory Particular topics on which new ideas and results are presented in these proceedings include: efficient schemes for combining networks, formal specification of shared memory models, correctness of trace-driven simulations,synchronization, various coherence protocols, .
Many modern computer systems, including homogeneous and heterogeneous architectures, support shared memory in hardware. In a shared memory system, each of the processor cores may read and write to a single shared address space. For a shared memory machine, the memory consistency model defines the architecturally visible behavior of its memory system. Consistency definitions provide rules about loads and stores (or memory reads and writes) and how they act upon memory. As part of supporting a memory consistency model, many machines also provide cache coherence protocols that ensure that multiple cached copies of data are kept up-to-date. The goal of this primer is to provide readers with a basic understanding of consistency and coherence. This understanding includes both the issues that must be solved as well as a variety of solutions. We present both high-level concepts as well as specific, concrete examples from real-world systems. This second edition reflects a decade of advancements since the first edition and includes, among other more modest changes, two new chapters: one on consistency and coherence for non-CPU accelerators (with a focus on GPUs) and one that points to formal work and tools on consistency and coherence.
The book illustrates state-of-the-art software solutions for cache coherence maintenance in shared-memory multiprocessors. It begins with a brief overview of the cache coherence problem and introduces software solutions to the problem. The text defines and details static and dynamic software schemes, techniques for modeling performance evaluation mechanisms, and performance evaluation studies.
Abstract: "In this paper, we study a hardware-supported, compiler-directed (HSCD) cache coherence scheme, which can be implemented on a large-scale multiprocessor using off-the-shelf microprocessors, such as the Cray T3D. The scheme can be adapted to various cache organizations, including multi-word cache lines and byte-addressable architectures. Several system related issues, including critical sections, inter-thread communication, and task migration have also been addressed. The cost of the required hardware support is minimal and proportional to the cache size. The necessary compiler algorithms, including intra- and interprocedural array data flow analysis, have been implemented on the Polaris parallelizing compiler [33]. From our simulation study using the Perfect Club benchmarks [5], we found that in spite of the conservative analysis made by the compiler, the performance of the proposed HSCD scheme can be comparable to that of a full-map hardware directory scheme. Given its comparable performance and reduced hardware cost, the proposed scheme can be a viable alternative for large-scale multiprocessors such as the Cray T3D, which rely on users to maintain data coherence."
The papers present in this text survey both distributed shared memory (DSM) efforts and commercial DSM systems. The book discusses relevant issues that make the concept of DSM one of the most attractive approaches for building large-scale, high-performance multiprocessor systems. The authors provide a general introduction to the DSM field as well as a broad survey of the basic DSM concepts, mechanisms, design issues, and systems. The book concentrates on basic DSM algorithms, their enhancements, and their performance evaluation. In addition, it details implementations that employ DSM solutions at the software and the hardware level. This guide is a research and development reference that provides state-of-the art information that will be useful to architects, designers, and programmers of DSM systems.