Reducing exception management overhead with software restart markers

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 181-196).Modern processors rely on exception handling mechanisms to detect errors and to implement various features such as virtual memory. However, these mechanisms are typically hardware-intensive because of the need to buffer partially-completed instructions to implement precise exceptions and enforce in-order instruction commit, often leading to issues with performance and energy efficiency. The situation is exacerbated in highly parallel machines with large quantities of programmer-visible state, such as VLIW or vector processors. As architects increasingly rely on parallel architectures to achieve higher performance, the problem of exception handling is becoming critical. In this thesis, I present software restart markers as the foundation of an exception handling mechanism for explicitly parallel architectures. With this model, the compiler is responsible for delimiting regions of idempotent code. If an exception occurs, the operating system will resume execution from the beginning of the region. One advantage of this approach is that instruction results can be committed to architectural state in any order within a region, eliminating the need to buffer those values. Enabling out-of-order commit can substantially reduce the exception management overhead found in precise exception implementations, and enable the use of new architectural features that might be prohibitively costly with conventional precise exception implementations. Additionally, software restart markers can be used to reduce context switch overhead in a multiprogrammed environment. This thesis demonstrates the applicability of software restart markers to vector, VLIW, and multithreaded architectures. It also contains an implementation of this exception handling approach that uses the Trimaran compiler infrastructure to target the Scale vectorthread architecture. I show that using software restart markers incurs very little performance overhead for vector-style execution on Scale.(cont.) Finally, I describe the Scale compiler flow developed as part of this work and discuss how it targets certain features facilitated by the use of software restart markersby Mark Jerome Hampton.Ph.D

Customizing the Computation Capabilities of Microprocessors.

Designers of microprocessor-based systems must constantly improve performance and increase computational efficiency in their designs to create value. To this end, it is increasingly common to see computation accelerators in general-purpose processor designs. Computation accelerators collapse portions of an application's dataflow graph, reducing the critical path of computations, easing the burden on processor resources, and reducing energy consumption in systems. There are many problems associated with adding accelerators to microprocessors, though. Design of accelerators, architectural integration, and software support all present major challenges. This dissertation tackles these challenges in the context of accelerators targeting acyclic and cyclic patterns of computation. First, a technique to identify critical computation subgraphs within an application set is presented. This technique is hardware-cognizant and effectively generates a set of instruction set extensions given a domain of target applications. Next, several general-purpose accelerator structures are quantitatively designed using critical subgraph analysis for a broad application set. The next challenge is architectural integration of accelerators. Traditionally, software invokes accelerators by statically encoding new instructions into the application binary. This is incredibly costly, though, requiring many portions of hardware and software to be redesigned. This dissertation develops strategies to utilize accelerators, without changing the instruction set. In the proposed approach, the microarchitecture translates applications at run-time, replacing computation subgraphs with microcode to utilize accelerators. We explore the tradeoffs in performing difficult aspects of the translation at compile-time, while retaining run-time replacement. This culminates in a simple microarchitectural interface that supports a plug-and-play model for integrating accelerators into a pre-designed microprocessor. Software support is the last challenge in dealing with computation accelerators. The primary issue is difficulty in generating high-quality code utilizing accelerators. Hand-written assembly code is standard in industry, and if compiler support does exist, simple greedy algorithms are common. In this work, we investigate more thorough techniques for compiling for computation accelerators. Where greedy heuristics only explore one possible solution, the techniques in this dissertation explore the entire design space, when possible. Intelligent pruning methods ensure that compilation is both tractable and scalable.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/57633/2/ntclark_1.pd