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Distributed saddle point problems (SPPs) have numerous applications in optimization, matrix games and machine learning. For example, the training of generated adversarial networks is represented as a min-max optimization problem, and training regularized linear models can be reformulated as an SPP as well. This paper studies distributed nonsmooth SPPs with Lipschitz-continuous objective functions. The objective function is represented as a sum of several components that are distributed between groups of computational nodes. The nodes, or agents, exchange information through some communication network that may be centralized or decentralized. A centralized network has a universal information aggregator (a server, or master node) that directly communicates to each of the agents and therefore can coordinate the optimization process. In a decentralized network, all the nodes are equal, the server node is not present, and each agent only communicates to its immediate neighbors.

We assume that each of the nodes locally holds its objective and can compute its value at given points, i. e. has access to zero-order oracle. Zero-order information is used when the gradient of the function is costly, not possible to compute or when the function is not differentiable. For example, in reinforcement learning one needs to generate a trajectory to evaluate the current policy. This policy evaluation process can be interpreted as the computation of the function value. We propose an approach that uses a smoothing technique, i. e., applies a first-order method to the smoothed version of the initial function. It can be shown that the stochastic gradient of the smoothed function can be viewed as a random two-point gradient approximation of the initial function. Smoothing approaches have been studied for distributed zero-order minimization, and our paper generalizes the smoothing technique on SPPs.

Algorithms of wireless sensor networks operation based on modified ZigBee/IEEE 802.15.4 protocol stack and problems of energy saving with simultaneous decrease of network latency are studied. Theoretical computations are given. Roles distribution and routers schedule assignment algorithms are described. Both results of experiments carried out with real devices and results of simulations with ns-2 (open-source network simulator) are given and analyzed.

Virtual machines are usually associated with an ability to create them on demand by calling web services, then these machines are used to deliver resident services to their clients; however, providing clients with an ability to run an arbitrary programme on the newly created machines is beyond their power. Such kind of usage is useful in a high performance computing environment where most of the resources are consumed by batch programmes and not by daemons or services. In this case a cluster of virtual machines is created on demand to run a distributed or parallel programme and to save its output to a network attached storage. Upon completion this cluster is destroyed and resources are released. With certain modifications this approach can be extended to interactively deliver computational resources to the user thus providing virtual desktop as a service. Experiments show that the process of creating virtual clusters on demand can be made efficient in both cases.

Independent components communicating with each other due to complex control make the work of complex distributed computer systems poorly scalable within the framework of the existing communication middleware. Two major problems of such systems' scaling can be defined: overloading of unequal nodes due to proportional redistribution of workload and difficulties in the realization of continuous communication between several nodes of the system. This paper is focused on the developed solution enabling visualization of the work of such a dynamical system.

The approach to build territorial distributed storage system for high performance computing environment of UB RAS is presented. The storage system is based on the dCache middleware from the European Middleware Initiative project. The first milestone of distributed storage system implementation includes the data centers at the two UB RAS Regions: Yekaterinburg and Perm.

Grid is a new type of computing infrastructure, is intensively developed in today world of information technologies. Grid provides global integration of information and computing resources. The essence Conception of GRID in Azerbaijan is to create a set of standardized services to provide a reliable, compatible, inexpensive and secure access to geographically distributed high-tech information and computing resources a separate computer, cluster and supercomputing centers, information storage, networks, scientific tools etc.