FPGA-based hardware accelerators for convolutional neural networks (CNNs) have obtained great attentions due to their higher energy efficiency than GPUs. However, it is challenging for FPGA-based solutions to achieve a higher throughput than GPU counterparts. In this paper, we demonstrate that FPGA acceleration can be a superior solution in terms of both throughput and energy efficiency when a ...

This paper focuses on production scheduling in a semiconductor wafer fab producing multiple product types that have different due dates and different process flows. In the wafer fab, wafer lots are processed on serial and batch processing workstations, each of which consists of parallel identical machines. Machines in serial processing workstations process wafer lots one by one, while those in ...

Quantitative target analysis by liquid chromatography coupled to mass spectrometry (LCMS) is ubiquitous in environmental, metabolomic and toxicological studies. Targeted LCMS methods are capable of the simultaneous determination of literally hundreds of analytes. Although acquiring of instrumental data is very fast, data post-processing i.e. quantification can be time consuming step (and)or dep...

This paper introduces a scheme for data stream processing which is robust to batch duration. Streaming frameworks process streams in batches retrieved at fixed time intervals. In a common setting a pattern recognition algorithm is applied independently to each batch. Choosing the right time interval is tough — a pattern may not fit in an interval which is too short, but detection will be delaye...

A batch machine is a machine that can process up to c jobs simultaneously as a batch, and the processing time of the batch is equal to the longest processing time of the jobs assigned to it. In this paper, we deal with the complexity of scheduling an unbounded batch machine, i.e., c = +∞. We prove that minimizing total tardiness is binary NP-hard, which has been an open problem in the literatur...

Cloud Computing is one of the emerging technologies. This research paper aimed to outline cloud computing and its features, and considered cloud computing for machine learning and data mining. The goal of the paper was to develop a recommendation and search system using big data platform on cloud environment. The main focus was on the study and understanding of Hadoop, one of the new technologi...

In this work, a novel sequence-based mixed-integer linear programming formulation for the simultaneous batching and scheduling in multi-product multi-stage batch plants is developed. The selection of batches, the allocation of batches to processing units and the sequencing of batches in each unit constitute the discrete decisions of our model. Batch processing times and sizes are variables. Bat...

Streaming capabilities are becoming increasingly important for scientific applications [1], [2] supporting important needs, such as the ability to act on incoming data and steering. The interoperable use of streaming data sources within HPC environments is a critical capability for an emerging set of applications. Scientific instruments, such as x-ray light sources (e. g., the Advanced Photon S...

We analyze batch-scheduling problems that arise in connection with certain industrial applications. The models concern processing on a single max-batch machine with the additional feature that the tasks of the same batch have to be compatible. Compatibility is a symmetric binary relation—the compatible pairs are described with an undirected “compatibility graph”, which is often an interval grap...