Instruction fetch architectures and code layout optimizations

The design of higher performance processors has been following two major trends: increasing the pipeline depth to allow faster clock rates, and widening the pipeline to allow parallel execution of more instructions. Designing a higher performance processor implies balancing all the pipeline stages to ensure that overall performance is not dominated by any of them. This means that a faster execution engine also requires a faster fetch engine, to ensure that it is possible to read and decode enough instructions to keep the pipeline full and the functional units busy. This paper explores the challenges faced by the instruction fetch stage for a variety of processor designs, from early pipelined processors, to the more aggressive wide issue superscalars. We describe the different fetch engines proposed in the literature, the performance issues involved, and some of the proposed improvements. We also show how compiler techniques that optimize the layout of the code in memory can be used to improve the fetch performance of the different engines described Overall, we show how instruction fetch has evolved from fetching one instruction every few cycles, to fetching one instruction per cycle, to fetching a full basic block per cycle, to several basic blocks per cycle: the evolution of the mechanism surrounding the instruction cache, and the different compiler optimizations used to better employ these mechanisms.Peer ReviewedPostprint (published version

MGSim - Simulation tools for multi-core processor architectures

MGSim is an open source discrete event simulator for on-chip hardware components, developed at the University of Amsterdam. It is intended to be a research and teaching vehicle to study the fine-grained hardware/software interactions on many-core and hardware multithreaded processors. It includes support for core models with different instruction sets, a configurable multi-core interconnect, multiple configurable cache and memory models, a dedicated I/O subsystem, and comprehensive monitoring and interaction facilities. The default model configuration shipped with MGSim implements Microgrids, a many-core architecture with hardware concurrency management. MGSim is furthermore written mostly in C++ and uses object classes to represent chip components. It is optimized for architecture models that can be described as process networks.Comment: 33 pages, 22 figures, 4 listings, 2 table

SCM : Secure Code Memory Architecture

An increasing number of applications implemented on a SoC (System-on-chip) require security features. This work addresses the issue of protecting the integrity of code and read-only data that is stored in memory. To this end, we propose a new architecture called SCM, which works as a standalone IP core in a SoC. To the best of our knowledge, there exist no architectural elements similar to SCM that offer the same strict security guarantees while, at the same time, not requiring any modifications to other IP cores in its SoC design. In addition, SCM has the flexibility to select the parts of the software to be protected, which eases the integration of our solution with existing software. The evaluation of SCM was done on the Zynq platform which features an ARM processor and an FPGA. The design was evaluated by executing a number of different benchmarks from memory protected by SCM, and we found that it introduces minimal overhead to the system

MFS: an Adaptive Distributed File System for Mobile Hosts

Mobility is a critical feature of computer systems, and while wireless networks are common, most applications that run on mobile hosts lack flexible mechanisms for data access in an environment with large and frequent variations in network connectivity. Such conditions arise, for example, in collaborative work applications, particularly when wireless and wired users share files or databases. In this paper, we describe some techniques for adapting data access to network variability in the context of MFS, a client cache manager for a distributed file system. We show how MFS is able to adapt to widely varying bandwidth levels through the use of modeless adaptation, and evaluate the benefit of mechanisms for improving file system performance and cache consistency using microbenchmarks and file system traces