Streaming Aggregation using Reconfigurable Hardware

High throughput and low latency streaming aggregation is essential for many applications that analyze massive volumes of data in real-time. In many cases, high speed stream aggregation can be achieved incrementally by computing partial results for multiple windows. However, for particular problems, temporarily storing all incoming raw data to a single window before processing is more efficient or even the only option. This thesis presents the first FPGA-based single window stream aggregation designs for tuple-based and time-based windowing policies. The proposed approach is able to support challenging queries required in realistic stream processing problems. More precisely, holistic, distributive, and algebraic aggregation functions, as well as custom ones can be supported. Our designs offer aggregation for large number of concurrently active keys and handles large window sizes and frequent aggregations. Maxeler\u27s dataflow engines (DFEs), which suit well the stream processing characteristics, are used to implement the designs. DFEs have a direct feed of incoming data from the network as well as direct access to off-chip DRAM. The tuple-based single window DFE processes up to 8 million tuples-per-second (1.1 Gbps) offering 1-2 orders of magnitude higher throughput than a state-of-the-art stream processing software system. The processing latency is less than 4 usec, 4 orders of magnitude lower latency than software. The time-based single-window stream aggregation DFE offers high processing throughput, up to 150 Mtuples/sec, similar to related GPU systems, which however do not support both time-based and single windows. It also offers an ultra-low processing latency of 1-10 usec, at least 4 orders of magnitude lower than software-based solutions

Reconfigurable-Hardware Accelerated Stream Aggregation

High throughput and low latency stream aggregation is essential for many applications that analyze massive volumes of data in real-time. Incoming data need to be stored in a single sliding-window before processing, in cases where incremental aggregations are wasteful or not possible at all. However, storing all incoming values in a single-window puts tremendous pressure on the memory bandwidth and capacity. GPU and CPU memory management is inefficient for this task as it introduces unnecessary data movement that wastes bandwidth. FPGAs can make more efficient use of their memory but existing approaches employ only on-chip memory and therefore, can only support small problem sizes (i.e. small sliding windows and number of keys) due to the limited capacity. This thesis addresses the above limitations of stream processing systems by proposing techniques for accelerating single sliding-window stream aggregation using FPGAs to achieve line-rate processing throughput and ultra low latency. It does so first by building accelerators using FPGAs and second, by alleviating the memory pressure posed by single-window stream aggregation. The initial part of this thesis presents the accelerators for both windowing policies, namely, tuple- and time-\ua0based, using Maxeler\u27s DataFlow Engines\ua0(DFEs) which have a direct feed of incoming data from the network as well as direct access to off-chip DRAM. Compared to state-of-the-art stream processing software system, the DFEs offer 1-2 orders of magnitude higher processing throughput and 4 orders of magnitude lower latency. The later part of this thesis focuses on alleviating the memory pressure due to the various steps in single-window stream aggregation. Updating the window with new incoming values and reading it to feed the aggregation functions are the two primary steps in stream aggregation. The high on-chip SRAM bandwidth enables line-rate processing, but only for small problem sizes due to the limited capacity. The larger off-chip DRAM size supports larger problems, but falls short on performance due to lower bandwidth. In order to bridge this gap, this thesis introduces a specialized memory hierarchy for stream aggregation. It employs Multi-Level Queues (MLQs) spanning across multiple memory levels with different characteristics to offer both high bandwidth and capacity. In doing so, larger stream aggregation problems can be supported at line-rate performance, outperforming existing competing solutions. Compared to designs with only on-chip memory, our approach supports 4 orders of magnitude larger problems. Compared to designs that use only DRAM, our design achieves up to 8x higher throughput. Finally, this thesis aims to alleviate the memory pressure due to the window-aggregation step. Although window-updates can be supported efficiently using MLQs, frequent window-aggregations remain a performance bottleneck. This thesis addresses this problem by introducing StreamZip, a dataflow stream aggregation engine that is able to compress the sliding-windows. StreamZip deals with a number of data and control dependency challenges to integrate a compressor in the stream aggregation pipeline and alleviate the memory pressure posed by frequent aggregations. In doing so, StreamZip offers higher throughput as well as larger effective window capacity to support larger problems. StreamZip supports diverse compression algorithms offering both lossless and lossy compression to fixed- as well as floating- point numbers. Compared to designs using MLQs, StreamZip lossless and lossy designs achieve up to 7.5x and 22x higher throughput, while improving the effective memory capacity by up to 5x and 23x, respectively

Evaluation of Different Organic Manure Mixtures in Vegetable Amaranth Cultivation

An investigation was conducted during 2009-2011 at College of Agriculture, Vellayani, to develop bio-organic composite manures containing at least 3%N, with N:K ratio of 1:0.5, and to evaluate the effect of these manures on growth and productivity of vegetables. The investigation comprised three separate experiments, namely, formulation and quality evaluation of bio-organic composite manures, mineralization of bio-organic composite manures, and, crop response study. Amaranth (Amaranthus tricolor) was raised as a test crop for the study. Organic sources used in the preparation of bio-organic composite manures were:coir pith compost, poultry manure, neem cake, ground nut cake, ash, rock dust and microbial consortium. Five composite organic manures, satisfying the selection criteria (3%N, N:K ratio of 1:0.5), were identified for further investigation. Results of the crop response study revealed that among the bio-organic composite manures used, maximum yield was obtained under poultry manure (50g)+ground nut cake(30g)+rock dust(19g)+microbial consortium (1g), and this was on par with (i) coir pith compost(50g)+ground nut cake(35g)+ash(15g), and, (ii) poultry manure (50g)+ground nut cake(30g)+rock dust(20g)

Data on polymorphism of XRCC1 and cervical cancer risk from South India

AbstractX-ray repair cross-complementing group 1 (XRCC1) is a major DNA repair gene involved in BER mutation. Polymorphisms in DNA repair genes associated with repair efficiency against DNA damage may predispose an individual׳s cancer susceptibility. Data from cervical cancer patients was collected from South Indian Women. Genotyping of XRCC1 polymorphisms (194C/T, 280G/A and 399G/A) was done by polymerase-chain-reaction with the confronting-two-pair primer (PCR-CTPP) method

Association of genetic markers with cardiomyopathy

Background: Cardiomyopathy is an anatomic and pathologic diagnosis associated with muscle or electrical dysfunction of the heart. Cardiomyopathies represent a heterogeneous group of diseases that often lead to progressive heart failure with significant morbidity and mortality. Cardiomyopathy and myocarditis resulted in 443,000 deaths in 2013 up from 294,000 in 1990. Objective:  The main objective of the present study is to observe the association of cardiomyopathy and genetic markers such as red cell enzymes namely, Esterase D [ESD] and Super oxide dismutase [SOD] and plasma proteins namely, Haptoglobin [HP] and Group specific component [GC] systems.Methods: In the present study, fifty cases presenting cardiomyopathy and fifty cases of age and sex matched healthy controls were included.  Red cell enzymes were determined by standard agarose gel electrophoresis. Plasma samples were typed using PAGE electrophoresis. The statistical significance of differences between patients and controls were tested. Analysis of the data was carried out using Epi Info 5 software. Relative risk was calculated by the random-effects method. For odds ratio, confidence interval was calculated. The significance level was 5%.Results: The inter group heterogeneity for ESD and SOD of red cell enzymes and GC system of plasma proteins was found to be a significant value (ESD: χ2 =10.2564; d.f. = 2; 0.01>p>0.001; SOD: χ2 = 11.1120; d.f. = 2; 0.01>p>0.001; GC: χ2 = 15.5044; d.f. = 2; p>0.001), when observed between cardiomyopathy patients and controls. Thus, all the examined groups were deviating from Hardy-Weinberg equilibrium indicating a significant association between cardiomyopathy and these red cell enzymes and plasma protein markers. There was a predominant occurrence of Haptoglobin 2 phenotype in patients when compared to controls. Risk estimates show significant association with both ESD and GC systems with an increased risk of 100% and more, indicating that individuals with ESD (2-2 and 2-1) and GC (2-1) phenotypes are more likely to get the disease when compared with the other phenotypes of the ESD and GC systems.Conclusions: Out of seven genetic markers, four markers (ESD, SOD, HP and GC) are found to be significant i.e. they show some relation with the cardiomyopathy which influences the disease. Furthermore studies on genetic markers, to be attempted in future, would certainly enlighten us to assess the role of these polymorphic systems in different cardiomyopathies.

Organic Farming Practices for Double-Sucker Planted Banana

An experiment was conducted at College of Agriculture, Vellayani, Kerala, during December 2009 to September 2012 to standardize organic farming practices for double-sucker planted tissue-culture raised banana var. Nendran. Treatments included three nutrient levels, (M1-133, M2-100 and M3-75% of recommended dose for tissue culture banana as organic), two times of application viz., T1- in two splits- (basal and 2MAP), and T2 in three splits (basal, 2 and 4 MAP) along with the Control (integrated nutrient management for double-sucker planted banana, i.e., FYM + 250:150:400g NPK pit-1). The experiment was laid out in Factorial RBD with three replications. Results of the study indicated that though 33% of additional nutrients were required for double-sucker planting along with INM, 100% of the dose was sufficient under organic farming for realizing a reasonable yield. Pooled analysis of gross income and net income revealed that organic production practices are also profitable in double-sucker planted banana

A forensic acquisition and analysis system for IaaS

Cloud computing is a promising next-generation computing paradigm that offers significant economic benefits to both commercial and public entities. Furthermore, cloud computing provides accessibility, simplicity, and portability for its customers. Due to the unique combination of characteristics that cloud computing introduces (including on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service), digital investigations face various technical, legal, and organizational challenges to keep up with current developments in the field of cloud computing. There are a wide variety of issues that need to be resolved in order to perform a proper digital investigation in the cloud environment. This paper examines the challenges in cloud forensics that are identified in the current research literature, alongside exploring the existing proposals and technical solutions addressed in the respective research. The open problems that need further effort are highlighted. As a result of the analysis of literature, it is found that it would be difficult, if not impossible, to perform an investigation and discovery in the cloud environment without relying on cloud service providers (CSPs). Therefore, dependence on the CSPs is ranked as the greatest challenge when investigators need to acquire evidence in a timely yet forensically sound manner from cloud systems. Thus, a fully independent model requires no intervention or cooperation from the cloud provider is proposed. This model provides a different approach to a forensic acquisition and analysis system (FAAS) in an Infrastructure as a Service model. FAAS seeks to provide a richer and more complete set of admissible evidences than what current CSPs provide, with no requirement for CSP involvement or modification to the CSP’s underlying architecture

Current and potential roles of immuno-PET/-SPECT in CAR T-cell therapy

Chimeric antigen receptor (CAR) T-cell therapies have evolved as breakthrough treatment options for the management of hematological malignancies and are also being developed as therapeutics for solid tumors. However, despite the impressive patient responses from CD19-directed CAR T-cell therapies, ~ 40%−60% of these patients' cancers eventually relapse, with variable prognosis. Such relapses may occur due to a combination of molecular resistance mechanisms, including antigen loss or mutations, T-cell exhaustion, and progression of the immunosuppressive tumor microenvironment. This class of therapeutics is also associated with certain unique toxicities, such as cytokine release syndrome, immune effector cell-associated neurotoxicity syndrome, and other “on-target, off-tumor” toxicities, as well as anaphylactic effects. Furthermore, manufacturing limitations and challenges associated with solid tumor infiltration have delayed extensive applications. The molecular imaging modalities of immunological positron emission tomography and single-photon emission computed tomography (immuno-PET/-SPECT) offer a target-specific and highly sensitive, quantitative, non-invasive platform for longitudinal detection of dynamic variations in target antigen expression in the body. Leveraging these imaging strategies as guidance tools for use with CAR T-cell therapies may enable the timely identification of resistance mechanisms and/or toxic events when they occur, permitting effective therapeutic interventions. In addition, the utilization of these approaches in tracking the CAR T-cell pharmacokinetics during product development and optimization may help to assess their efficacy and accordingly to predict treatment outcomes. In this review, we focus on current challenges and potential opportunities in the application of immuno-PET/-SPECT imaging strategies to address the challenges encountered with CAR T-cell therapies

Impact of Detectable Monoclonal Protein at Diagnosis on Outcomes in Marginal Zone Lymphoma: A Multicenter Cohort Study

Given the paucity of data surrounding the prognostic relevance of monoclonal paraprotein (M-protein) in marginal zone lymphoma (MZL), we sought to evaluate the impact of detecting M-protein at diagnosis on outcomes in patients with MZL in a large retrospective cohort. The study included 547 patients receiving first-line therapy for MZL. M-protein was detectable at diagnosis in 173 (32%) patients. There was no significant difference in the time from diagnosis to initiation of any therapy (systemic and local) between the M-protein and no M-protein groups. Patients with M-protein at diagnosis had significantly inferior progression-free survival (PFS) compared with those without M-protein at diagnosis. After adjusting for factors associated with inferior PFS in univariate models, presence of M-protein remained significantly associated with inferior PFS (hazard ratio, 1.74; 95% confidence interval, 1.20-2.54; P = .004). We observed no significant difference in the PFS based on the type or quantity of M-protein at diagnosis. There were differential outcomes in PFS based on the first-line therapy in patients with M-protein at diagnosis, in that, those receiving immunochemotherapy had better outcomes compared with those receiving rituximab monotherapy. The cumulative incidence of relapse in stage 1 disease among the recipients of local therapy was higher in the presence of M-protein; however, this did not reach statistical significance. We found that M-protein at diagnosis was associated with a higher risk of histologic transformation. Because the PFS difference related to presence of M-protein was not observed in patients receiving bendamustine and rituximab, immunochemotherapy may be a preferred approach over rituximab monotherapy in this group and needs to be explored further