相关论文: Minimalist's Linux Cluster
We present extended multi block approach in the LIPI Public Cluster. The multi block approach enables a cluster to be divided into several independent blocks which run jobs owned by different users simultaneously. Previously, we have…
Evaluation of large-scale network systems and applications is usually done in one of three ways: simulations, real deployment on Internet, or on an emulated network testbed such as a cluster. Simulations can study very large systems but…
We present a novel clustering algorithm, visClust, that is based on lower dimensional data representations and visual interpretation. Thereto, we design a transformation that allows the data to be represented by a binary integer array…
A key challenge in scaling shared-L1 multi-core clusters towards many-core (more than 16 cores) configurations is to ensure low-latency and efficient access to the L1 memory. In this work we demonstrate that it is possible to scale up the…
In this paper, we propose a set of operating system primitives which provides a scaling abstraction to cloud applications in which they can transparently be enabled to support scaled execution across multiple physical nodes as resource…
We give evidence that particles interacting via the simple, radially symmetric square-shoulder potential can self-organize in highly complex, low-symmetry lattices, forming thereby clusters, columns, or lamellae; only at high pressure…
Traditionally, multithreaded data structures have been designed for access by the threads of Operating Systems (OS). However, implementations for access by programmable alternatives known as lightweight threads (also referred to as…
We present the v1.0 release of CLMM, an open source Python library for the estimation of the weak lensing masses of clusters of galaxies. CLMM is designed as a standalone toolkit of building blocks to enable end-to-end analysis pipeline…
Low-code platforms (latest reincarnation of the long tradition of model-driven engineering approaches) have the potential of saving us countless hours of repetitive boilerplate coding tasks. However, as software systems grow in complexity,…
A high performance Beowulf (PC cluster) machine installed with Linux operating system and MPI (Message Passing Interface) for interprocessor communications has been constructed using Gigabit Ethernet and the communication software GAMMA…
Cloud computing provides a great opportunity for scientists, as it enables large-scale experiments that cannot are too long to run on local desktop machines. Cloud-based computations can be highly parallel, long running and data-intensive,…
With the growing use of embedded systems in various industries, the need for automated platforms for the development and deployment of customized Linux-based operating systems has become more important. This research was conducted with the…
A new approach for designing bilayer and multi-layer LDPC codes is proposed and studied in the asymptotic regime. The ensembles are defined through individual uni-variate degree distributions, one for each layer. We present a construction…
The progression of scientific computing resources has enabled the numerical approximation of mathematical models describing complex physical phenomena. A significant portion of researcher time is typically dedicated to the development of…
Muntjac is an open-source collection of components which can be used to build a multicore, Linux-capable system-on-chip. This includes a 64-bit RISC-V core, a cache subsystem, and TileLink interconnect allowing cache-coherent multicore…
The demands on networks are increasing at a fast pace. In particular, real-time applications have very strict network requirements. However, building a network that hosts real-time applications is a cost-intensive endeavor, especially for…
The DEEP projects have developed a variety of hardware and software technologies aiming at improving the efficiency and usability of next generation high-performance computers. They evolve around an innovative concept for heterogeneous…
Transformer-based architectures are the model of choice for natural language understanding, but they come at a significant cost, as they have quadratic complexity in the input length, require a lot of training data, and can be difficult to…
With the current trend of multiprocessor machines towards more and more hierarchical architectures, exploiting the full computational power requires careful distribution of execution threads and data so as to limit expensive remote memory…
Plasma is a framework for scalable off-chain computation. We describe and evaluate Plasma Cash, an improved Plasma construction which leverages non-fungible tokens and Sparse Merkle Trees to reduce the data storage and bandwidth…