A Qualitative Study Investigating How First-Year Engineering Students\u27 Value Beliefs Influence their Choice of Selecting an Engineering Major

First year engineering (FYE) programs are gaining popularity across universities in the United States. In addition to providing general engineering knowledge and skills to undergraduate freshmen, FYE programs also provide students with diverse opportunities to help them select the engineering discipline they will further pursue. The 2014 cohort of the FYE program of a large Midwestern university was the sample used for a two-phased study. The aim of the study was to understand how students make informed decisions of which engineering major to pursue and to help FYE administration to improve the resources they provide students. The first phase of the study focused on understanding the sources of information students used to make their decision. A preliminary analysis of student surveys indicated that the most important activity they are performing to select a major is “Self-Led Exploration” (SLE) of engineering disciplines. This paper focuses on the second part of the study, which aims to qualitatively answer the research question: How do students’ value beliefs influence their decision of which engineering major to pursue? Answers to open ended questions from FYE surveys also served to inform this second study. Moreover, a brief examination of both the interviews and the surveys suggested a possible overlapping between the sources students used to inform their decision and the reasons why they selected a particular major. From that overlap, a secondary research question emerged: What is the relation between students’ value beliefs of the engineering disciplines and the type of sources they use to inform their decision of a major? To analyze our transcripts we used Eccle’s expectancy-value theory. We hypothesize that students’ value beliefs, how well a task aligns with their personal values, goals, and needs, influences their career choice and the type of resources they use to inform themselves

Exploiting intra-warp address monotonicity for fast memory coalescing in GPUs

Graphics Processing Units (GPUs) are growing increasingly popular as general purpose compute accelerators. GPUs are best suited for applications which have abundant data parallelism wherein the computation expressed as a single thread can be applied over a large set of data items. One key constraint that affects application performance on GPUs is that the underlying hardware is single-instruction, multiple data (SIMD) hardware which requires parallel instructions from the multiple threads to execute in a lock-step manner. The benefits of lock-step execution can be seriously degraded if the threads diverge (because of memory or branches). Specifically in the case of memory, the addresses from each thread in a SIMD wavefront/warp must be coalesced to enable parallel memory access to minimize divergence. The general problem of coalescing assumes arbitrary address distribution which can be slow. This thesis aims to exploit intra-warp address monotonicity (as measured in a recent study by Holic) to achieve fast memory coalescing. Holic\u27s study reveals the intra-warp addresses are monotonically increasing or decreasing in the common case. The key contributions of this thesis are twofold. First, I design novel hardware coalescing mechanisms to achieve fast-coalescing and quantify the area/delay of my coalescing designs. Second, I quantify the impact of fast-coalescing on overall GPU performance for a suite of GPU benchmarks