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DIstributed Computing Environments (DICE) Team
We are a group of computer scientists and IT experts from the Department of Computer Science AGH and ACC Cyfronet AGH. We are a curiosity- and research-driven team, specializing in large-scale distributed computing, HPC, Web and Cloud technologies. We develop new methods, tools and environments and we apply these solutions in e-Science, healthcare and industrial domains.

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Performance evaluation of cloud functions

Cloud Functions, often called Function-as-a-Service (FaaS), pioneered by AWS Lambda, are an increasingly popular method of running distributed applications. We developed a cloud function benchmarking framework, based on Serverless Framework, and we evaluated all the major cloud function providers: AWS Lambda, Azure Functions, Google Cloud Functions and IBM OpenWhisk. We make our results available online and continuously updated at

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RESTful (r)evolution for science gateways using HPC resources

This blog entry presents a service which allows to access HPC (high performance computing) resources via a REST interface taking care of all the underlying software stacks (job management using various middleware libraries and file transfers). As a result integration with the resources is plain and simple by using dominant web protocols with platform independence as a first-class citizen. The entry assumes a reader has basic knowledge of Grid job management specifics.

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To bake or not to bake - or how to create VM images in hybrid clouds.

Public, private and hybrid clouds of IaaS model give you the root access to the virtual machine instances and the power to install everything you need, apply all the tweaks to the OS and applications, and save the VM image as a new template. The question arises: when I change something, should I save it as a new template again - we call it “baking” a new image; or maybe I should have a set of scripts - we call it a devops way - to automate the installation process and apply it to a fresh image? Should I bake or should I not? Unsurprisingly, both ways have pros and cons.

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Taming [meta]data with DataNet, a PaaS case study

Description and thoughts that lead to creation of DataNet, a lightweight data and metadata management platform, exposed as a service. DataNet was designed so its usage yields better data availability, discoverability, easier access and sharing, compared to work done on plain files or databases.

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Multisupport for Multiscale

Modern scientists are commonly faced with the challenge of modeling and simulating multiscale systems where several processes with differing scales interact. At DICE we have been developing support for simulating such systems. We aim at multiscale applications that can be described as a set of interconnected single-scale modules, i.e. modules that implement single-scale process models. Each application run may involve many invocations of a single-scale module. At the modeling stage such multiscale applications can be represented in the form of a coupling topology - a graph with instances of single-scale models as its nodes. Typically, constructing multiscale applications is not trivial and requires a lot of effort on the part of application designers. To support development of multiscale applications and facilitate their execution we have developed a set of tools, presented below.

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Between SaaS and PaaS: Framework as a Service

Utility computing, where everything is a service, is here to stay. And it’s no longer just the bigger or smaller SaaS, PaaS and IaaS offerings. More specialized yet exciting high-quality services are becoming increasingly popular: databases as a service (irisouch), app components as a service (maps), or even development IDE as a service (cloud9). In the DICE team we have been developing a software platform for early warning systems for natural disasters – the Common Information Space ( At first CIS assumed the shape of a typical software framework: a bunch of tools, APIs and runtime services to assist in development, deployment and execution of early warning systems. Yet as time went by another idea grew on our minds: can we make the whole thing a service? That’s how the concept of a Framework as a Service emerged…

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Data Waterfall Floods a Poor Little DB

How far can one go with a single MySQL db instance? When faced with a waterfall of bioinformatics data, how much is "too much"? Today we'd like to tell a tale of a real bioinformatics application which, quite simply, ended up producing too much data. We describe what we did in order to make the data manageable with a single SQL database, what lengths we had to go to to get there and, finally, why we never really got there after all.

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Living publications - are they possible?

The lifecycle of modern publications is composed of the following steps: creating an abstract, submitting a full paper and publishing an article on the publisher's webpage where it can be read. This model is arguably sufficient when browsing for new content but what if the reader would like to look deeper and experiment with the method or tools described in the publication?

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Can cloud computing be free?

Everybody knows that one of the features of cloud computing is "pay-per-use". People are convinced, that although prices may drop, cloud will never be free (see e.g. On the other hand, Google, Amazon, Apple, Microsoft and many others are offering some cloud services for free. The question is how much we can actually get for free. This is what we tried to measure.

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DICE Team announces a new blog

Why DICE Blog? Don’t we have enough publications, presentations, posters, leaflets, reports, manuals, movies and tons of software on our website? Isn’t that enough to share our ideas?

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