Optimizing Program Efficiency with Loop Unroll Factor Prediction

Loop unrolling is a well-established code transformation technique that can improve the performance of a program at runtime. The key benefit of unrolling a loop is that it often requires fewer instruction executions than the original loop. However, determining the optimal number of loop unrolling is a critical concern. This paper presents a novel method for predicting the optimal unroll factor for a given program. Specifically, a dataset is constructed that includes the execution times of several programs with varying loop unroll factors. The programs are sourced from different benchmarks, such as Ploybench, Shooutout, and other programs. Similarity measures between the unseen program and the existing programs are computed, and the three most similar programs are identified. The unroll factor that led to the greatest reduction in execution time for the most similar programs is selected as the candidate for the unseen program. Experimental results demonstrate that the proposed method can enhance the performance of training programs for unroll factors of 2, 4, 6, and 8 by approximately 13%, 18%, 19%, and 21%, respectively. For the unseen programs, the speedup rate is approximately 37.7% for five programs

Differential proteomic study of oil palm leaves in response to in vitro inoculation with pathogenic and non-pathogenic Ganoderma spp.

Basal stem rot is an aggressive disease in oil palm caused by Ganoderma species. The disease threatens the commercial oil palm plantations of South East Asia, especially in Malaysia. In order to understand the mechanism involved in the early stage of interaction between Ganoderma spp. and its host at systemic level, proteomic analysis of oil palm leaves was conducted on protein samples collected over 72 hours during inoculation with pathogenic Ganoderma boninense and non-pathogenic Ganoderma tornatum. A total of 82 proteins resolved during two-dimensional gel electrophoresis with significant differences in the spot abundance. However, only 24 differentially expressed proteins in response to Ganoderma spp. inoculations were successfully identified by mass spectrophotometry as compared to the non-inoculated control. These proteins are mainly involved in photosynthesis, signalling, stress/defense, energy and metabolism regulation. Changes in relative abundance of these proteins suggest an important role in disease susceptibility. Most proteins showed altered abundance in response to both G. boninense and G. tornatum, while some proteins were only affected by either G. boninense or G. tornatum. The putative role of the identified proteins in oil palm leaves during the interaction with both Ganoderma spp. is discussed

Comparative proteomic analysis of Ganoderma species during in vitro interaction with oil palm root

Basal stem rot disease caused by Ganoderma spp. is still considered a large threat to oil palm production in many countries, especially in Malaysia, which contributes to approximately 45% of the world's palm oil exports. In the last 10 years, studies on the oil palm-Ganoderma interaction have mainly focused on the response of the plant towards the fungus. In this study, a comparative proteomic analysis was conducted to investigate the change in protein expression of two Ganoderma spp., namely Ganoderma boninense, which is known as the most aggressive species and Ganoderma tornatum, previously reported as non-pathogenic. Our results showed that both species colonize and penetrate the oil palm root after only 72 h of inoculation. In addition, proteins were expressed differentially in both species that have either direct or indirect links to virulence and pathogenicity. Other proteins related to fungal growth, metabolism and stress from both species were also discussed in this study