Students in all areas of computing require knowledge of the computing device including software implementation at the machine level. Several courses in computer science curricula address these low-level details such as computer architecture and assembly languages. For such courses, there are advantages to studying real architectures instead of simplified examples. However, real architectures and instruction sets introduce complexity that makes them difficult to grasp in a single semester course. Visualization techniques can help ease this burden, unfortunately existing tools are often difficult to use and consequently difficult to adopt in a course where time is already limited. To solve this problem, we present Frances. Frances graphically illustrates key differences between familiar high-level languages and unfamiliar low-level languages and also illustrates how familiar high-level programs behave on real architectures. Key to this tool is that we use a simple Web interface that requires no setup, easing course adoption hurdles. We also include several features that further enhance its usefulness in a classroom setting. These features include graphical relationships between high-level code and machine code, clearly illustrated step-by-step machine state transitions, color coding to make instruction behavior clear, and illustration of pointers. We have used Frances in courses and performed experimental evaluation. Our experiences with Frances in the classroom demonstrate its usability. Most notably, in our experimental setting, students with no computer architecture course experience were able to complete lessons using Frances with no guidance.

The latest trend towards performance asymmetry among cores on a single chip of a multicore processor is posing new challenges. For effective utilization of these performance-asymmetric multicore processors, code sections of a program must be assigned to cores such that the resource needs of code sections closely matches resource availability at the assigned core. Determining this assignment manually is tedious, error prone, and significantly complicates software development. To solve this problem, we contribute a transparent and fully-automatic process that we call phase-based tuning which adapts an application to effectively utilize performance-asymmetric multicores. Compared to the stock Linux scheduler we see a 36% average process speedup, while maintaining fairness and with negligible overheads.

Writing correct and efficient concurrent programs still remains a challenge. Explicit concurrency is difficult, error prone, and creates code which is hard to maintain and debug. This type of concurrency also treats modular program design and concurrency as separate goals, where modularity often suffers. To solve these problems, we are designing a new language that we call Panini. In this paper, we focus on Panini's asynchronous, typed events which reconcile the modularity goal promoted by the implicit invocation design style with the concurrency goal of exposing potential concurrency between the execution of subjects and observers.

As demand for computational power of embedded applications has increased, their architectures have become more complex. One result of this increased complexity are real-time embedded systems with set-associative multi-level caches. Multi-level caches complicate the process of program analysis techniques such as worst case execution time (WCET). To address this need we have developed a sound cache behavior analysis that handles multi-level instruction and data caches. Our technique relies on a new abstraction, live caches, which models relationships between cache levels to improve accuracy. Our analysis improves upon previous multi-level cache analysis in three ways. First, it handles write-back, a common feature of cache models, soundly. Second, it handles both instruction and data cache hierarchies, and third, it improves precision of cache analysis. For standard WCET benchmarks and a multi-level cache configuration analyzed by previous work, we observed that live caches improve WCET precision resulting in an average of 6.3% reduction in computed WCET.

Compiler and programming language implementation courses are integral parts of many computer science curricula. However, the range of topics necessary to teach in such a course are difficult for students to understand and time consuming to cover. In particular, code generation is a confusing topic for students unfamiliar with low level target languages. We present Frances, a tool for helping students understand code generation and low level languages. The key idea is to graphically illustrate the relationships between high level language constructs and low level (assembly) language code. By illustrating these relationships, we take advantage of the students existing understanding of some high level language. We have used Frances in a compiler design course and received highly positive feedback. Students conveyed to us that Frances significantly helped them to understand the concepts necessary to implement code generation in a compiler project.

As multi-core processors are becoming common, vendors are starting to explore trade offs between the die size and the number of cores on a die, leading to heterogeneity among cores on a single chip. For efficient utilization of these processors, application threads must be assigned to cores such that the resource needs of a thread closely matches resource availability at the assigned core. Current methods of thread-to-core assignment often require an application's execution trace to determine its runtime properties. These traces are obtained by running the application on some representative input. A problem is that developing these representative input sets is time consuming, and requires expertise that the user of a general-purpose processor may not have. We propose an approach for automatic thread-to-core assignment for heterogeneous multicore processors to address this problem. The key insight behind our approach is simple - if two phases of a program are similar, then the data obtained by dynamic monitoring of one phase can be used to make scheduling decisions about other similar phases. The technical underpinnings of our approach include: a preliminary static analysis-based approach for determining similarity among program sections, and a thread-to-core assignment algorithm that utilizes the statically generated information as well as execution information obtained from monitoring a small fraction of the program to make scheduling decisions.