Limits of Data Level Parallelism

Abstract—A new breed of processors like the Cell Broadband Engine, the Imagine stream processor and the various GPU processors emphasize data-level parallelism (DLP) and threadlevel parallelism (TLP) as opposed to traditional instructionlevel parallelism (ILP). This allows them to achieve order-ofmagnitude improvements over conventional superscalar processors for many workloads. However, it is unclear as to how much parallelism of these types exists in current programs. Most earlier studies have largely concentrated on the amount of ILP in a program, without differentiating DLP or TLP. In this study, we investigate the extent of data-level parallelism available in programs in the MediaBench suite. By packing instructions in a SIMD fashion, we observe reductions of up to 91 % (84 % on average) in the number of dynamic instructions, indicating a very high degree of DLP in several applications. I.

Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: multi-scale approach

Human Leukocyte Antigen (HLA) plays an important role, in presenting foreign pathogens to our immune system, there by eliciting early immune responses. HLA genes are highly polymorphic, giving rise to diverse antigen presentation capability. An important factor contributing to enormous variations in individual responses to diseases is differences in their HLA profiles. The heterogeneity in allele specific disease responses decides the overall disease epidemiological outcome. Here we propose an agent based computational framework, capable of incorporating allele specific information, to analyze disease epidemiology. This framework assumes a SIR model to estimate average disease transmission and recovery rate. Using epitope prediction tool, it performs sequence based epitope detection for a given the pathogenic genome and derives an allele specific disease susceptibility index depending on the epitope detection efficiency. The allele specific disease transmission rate, that follows, is then fed to the agent based epidemiology model, to analyze the disease outcome. The methodology presented here has a potential use in understanding how a disease spreads and effective measures to control the disease.

The basics and advances of immunomodulators and antigen presentation: a key to development of potent memory response against pathogens

Introduction: Immunomodulators are agents, which can modulate the immune response to specific antigens, while causing least toxicity to the host system. Being part of the modern vaccine formulations, these compounds have contributed remarkably to the field of therapeutics. Despite the successful record maintained by these agents, the requirement of novel immunomodulators keeps increasing due to the increasing severity of diseases. Hence, research regarding the same holds great importance. Areas covered: In this review, we discuss the role of immunomodulators in improving performance of various vaccines used for counteracting most threatening infectious diseases, mechanisms behind their action and criteria for development of novel immunomodulators. Expert opinion: Understanding the molecular mechanisms underlying immune response is a prerequisite for development of effective therapeutics as these are often exploited by pathogens for their own propagation. Keeping this in mind, the present research in the field of immunotherapy focuses on developing immunomodulators that would not only enhance the protection against pathogen, but also generate a long-term memory response. With the introduction of advanced formulations including combination of different kinds of immunomodulators, one can expect tremendous success in near future.