ZA

199 records found

This paper introduces TINA, a novel framework for implementing non Neural Network (NN) signal processing algorithms on NN accelerators such as GPUs, TPUs or FPGAs. The key to this approach is the concept of mapping mathematical and logic functions as a series of convolutional and ...

Hardware-Accelerator Design by Composition

Dataflow Component Interfaces with Tydi-Chisel

As dedicated hardware is becoming more prevalent in accelerating complex applications, methods are needed to enable easy integration of multiple hardware components into a single accelerator system. However, this vision of composable hardware is hindered by the lack of standards ...
In this paper, we present a fully pipelined and semi-parallel channel convolutional neural network hardware accelerator structure. This structure can trade off the compute time and the hardware utilization, allowing the accelerator to be layer pipelined without the need for fully ...

Beyond quantum Shannon decomposition

Circuit construction for n -qubit gates based on block- ZXZ decomposition

This paper proposes an optimized quantum block-ZXZ decomposition method that results in more optimal quantum circuits than the quantum Shannon decomposition, which was presented in 2005 by M. Möttönen, and J. J. Vartiainen [in Trends in quantum computing research, edited by S. Sh ...
In spite of progress on hardware design languages, the design of high-performance hardware accelerators forces many design decisions specializing the interfaces of these accelerators in ways that complicate the understanding of the design and hinder modularity and collaboration. ...
Tydi is an open specification for streaming dataflow designs in digital circuits, allowing designers to express how composite and variable-length data structures are transferred over streams using clear, data-centric types. These data types are extensively used in a many applicat ...
Background

Non-Invasive Prenatal Testing is often performed by utilizing read coverage-based profiles obtained from shallow whole genome sequencing to detect fetal copy number variations. Such screening typically operates on a discretized binned representation of the gen ...
Convolutional neural networks (CNNs) are to be effective in many application domains, especially in the computer vision area. In order to achieve lower latency CNN processing, and reduce power consumption, developers are experimenting with using FPGAs to accelerate CNN processing ...
Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, clients would upload their updated models to the blockchain ledger and use a smart contract to perform ...
This paper offers a systematic method for creating medical knowledge-grounded patient records for use in activities involving differential diagnosis. Additionally, an assessment of machine learning models that can differentiate between various conditions based on given symptoms i ...

QKSA

Quantum Knowledge Seeking Agent

In this research, we extend the universal reinforcement learning agent models of artificial general intelligence to quantum environments. The utility function of a classical exploratory stochastic Knowledge Seeking Agent, KL-KSA, is generalized to distance measures from quantum i ...
Motion prediction is a key factor towards the full deployment of autonomous vehicles. It is fundamental in order to assure safety while navigating through highly interactive complex scenarios. In this work, the framework IAMP (Interaction-Aware Motion Prediction), producing multi ...
Moving structured data between different big data frameworks and/or data warehouses/storage systems often cause significant overhead. Most of the time more than 80% of the total time spent in accessing data is elapsed in serialization/de-serialization step. Columnar data formats ...

BioDynaMo

A modular platform for high-performance agent-based simulation

Motivation: Agent-based modeling is an indispensable tool for studying complex biological systems. However, existing simulation platforms do not always take full advantage of modern hardware and often have a field-specific software design. Results: We present a novel simulation p ...

WisecondorFF

Improved Fetal Aneuploidy Detection from Shallow WGS through Fragment Length Analysis

In prenatal diagnostics, NIPT screening utilizing read coverage-based profiles obtained from shallow WGS data is routinely used to detect fetal CNVs. From this same data, fragment size distributions of fetal and maternal DNA fragments can be derived, which are known to be differe ...

SALoBa

Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs

Sequence alignment forms an important backbone in many sequencing applications. A commonly used strategy for sequence alignment is an approximate string matching with a two-dimensional dynamic programming approach. Although some prior work has been conducted on GPU acceleration o ...
Unitary decomposition is a widely used method to map quantum algorithms to an arbitrary set of quantum gates. Efficient implementation of this decomposition allows for the translation of bigger unitary gates into elementary quantum operations, which is key to executing these algo ...
Current cluster scaled genomics data processing solutions rely on big data frameworks like Apache Spark, Hadoop and HDFS for data scheduling, processing and storage. These frameworks come with additional computation and memory overheads by default. It has been observed that scali ...

WhiskEras 2.0

Fast and Accurate Whisker Tracking in Rodents

Mice and rats can rapidly move their whiskers when exploring the environment. Accurate description of these movements is important for behavioral studies in neuroscience. Whisker tracking is, however, a notoriously difficult task due to the fast movements and frequent crossings a ...