Faculty of Computer Science and Engineering

Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5

The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest faculties in that field in the region. The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.

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Transformer-based heart language model with electrocardiogram annotations
(Springer Science and Business Media LLC, 2025-02-14)
Tudjarski, Stojancho
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Kanoulas, Evangelos
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Small Prompts, Big Energy and CO2 Impact: Benchmarking Ollama LLMs on CPU and GPU
(IEEE, 2025-11-25)
Kolovska, Ana
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Gusev, Marjan
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Mileski, Dimitar
Energy efficiency is a crucial challenge when deploying Large Language Models (LLMs). Electricity usage and related CO2 emissions can differ greatly depending on model architecture, parameter size, prompt length, and inference hardware. In this study, we evaluate 31 popular Ollama models across CPU and GPU inference, resulting in 60 testing scenarios. Energy and carbon metrics were gathered using the NVML and CodeCarbon libraries, providing insights into the environmental impact of LLM inference in data center settings.
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Loop Unrolling Impact on CUDA Matrix Multiplication Operations
(IEEE, 2024-11-26)
Stefkovski, Vojdan
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Mileski, Dimitar
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Gusev, Marjan
This paper investigates the impact of loop unrolling on CUDA matrix multiplication operations’ performance across NVIDIA GPUs. We benchmarked both basic and unrolled kernels with varying unroll factors (2, 4, 8, and 16) and CUDA block sizes (8, 16, and 32) on matrices ranging from 128 × 128 to 4096 × 4096. Using two GPUs, the GeForce RTX 4060 and GTX TITAN X, we analyze how unrolling factors impact execution time. Our findings indicate that loop unrolling, particularly with factors of 8 and 16 and a block size of 32, yields significant performance gains on larger matrices. These results confirm loop unrolling as an effective optimization technique for CUDA matrix operations, providing insights for developers to enhance computational efficiency across different GPU architectures.
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CUDA Calculation of Shannon Entropy for a Sliding Window System
(IEEE, 2024-11-26)
Velichkovski, Gordon
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Gusev, Marjan
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Mileski, Dimitar
Entropy algorithms are crucial in fields where assessing randomness, uncertainty, or complexity is vital. As datasets grow, efficient entropy calculations become important. This work explores the parallelization of Shannon entropy calculations, using GPU acceleration through CUDA for sliding window systems. By leveraging GPUs’ parallel architecture, the approach achieves up to 15x speedup for large datasets. However, smaller datasets show limited improvements due to overhead, underscoring the need for optimization to harness GPU acceleration’s potential.
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Optimal Scalable Real-Time ECG Monitoring of Thousands of Concurrent Patients
(IEEE, 2024-05-20)
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Gushev, Pano
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This paper explores the transformation of electrocardiogram (ECG) monitoring from traditional offline to Real-Time analysis, enabled by high-speed mobile networks and affordable data plans. The transition to live monitoring presents challenges in data streaming and processing and the necessity of balancing immediacy with accuracy. We optimize two critical aspects of cloud architecture and scalability under the broader umbrella of cloud efficiency by evaluating the architecture’s components and their contribution to overall efficiency. The focus is on accommodating over a thousand concurrent patients streaming ECG data while maintaining cost-effectiveness, constrained by Near Real-Time Round Trip Time (RTT) of ≤ 3 seconds, achieving a throughput of ≥ 333.333 (msgs/s).
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Architecture of a Distributed Infrastructureless System
(IEEE, 2024-05-20)
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Recent trends in the production of portable devices, such as smartphones, smartwatches, and all other smart devices, show that their computing resources are comparable to laptops and desktop computers produced several years ago. In addition, many installed IoT devices around us realize that pervasive and ubiquitous computing integrates a remarkable amount of computing power. Unfortunately, these computing resources efficiently comply with the ever-increasing demand for computing power. Realizing a system that integrates devices on more minor architectural levels (IoT and edge layers) is a complex and challenging task, especially if the system goes beyond edge computing toward autonomous processing and realizes the essence of dew computing. The system should be platform-agnostic and provider-agnostic so all surrounding devices may participate and build more powerful computing resources. Finally, the proposed system realizes Infrastructureless computing, integrating Serverless, Deviceless, and Thingless computing as a service to nearby consumers. This paper analyzes the architecture of such a distributed computing system.
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Serverless electrocardiogram stream processing in federated clouds with lambda architecture
(IEEE, 2023-08-18)
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Gusev, Marjan
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Hohenegger, Armin
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Prodan, Radu
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Mileski, Dimitar
In this article, we explore a novel architecture for distributing health monitoring computations over distributed cloud regions, both for constantly online patients and offline for several hours daily. We propose a conceptual architecture for a use-case example capable of processing thousands of simultaneous incoming streams with electrocardiogram signals.
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Scalable Dew Computing
(MDPI, 2022-09-22)
Gusev, Marjan
Dew computing differs from the classical cloud and edge computing by bringing devices closer to the end-users and adding autonomous processing independent from the Internet, but it is still able to collaborate with other devices to exchange information on the Internet. The difference is expressed also on scalability, since edge and cloud providers can provide (almost endless) resources, and in the case of dew computing the scalability needs to be realized on the level of devices, instead of servers. In this paper, we introduce an approach to provide deviceless and thingless computing and ensure scalable dew computing. The deviceless approach allows functions to be executed on nearby devices found closer to the user, and the thingless approach goes even further, providing scalability on a low-level infrastructure that consists of multiple things, such as IoT devices. These approaches introduce the distribution of computing to other smart devices or things on a lower architectural level. Such an approach enhances the existing dew computing architectural model as a sophisticated platform for future generation IoT systems.
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M-government framework
(2005)
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M-government is largely a matter of getting public sector IT systems geared to interoperability with citizen’s mobile devices. In this regard, developing a coherent m-government framework in the public sector is an important factor. The basic concept for good framework is that it is principle-driven. A common mobile public services framework must first and foremost incorporate the following five principles: Interoperability, Security, Openness, Flexibility and Scalability. A short survey report for Macedonia is presented, with special attention in bridging the digital divide among developing and developed countries. As the survey in Macedonia has shown, the citizens should be carefully educated in order to feel comfortable with m-government. It involves public campaign and benefits that the citizens can clearly see and understand. Key points of innovative ideas and views for further research and development in this field is sketched in the paper
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Scanning of services based on E-Governance Macedonia 2020
(Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia, 2020-05-08)
Kitanov, Boshko
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Ibraimi, Gzim
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Gusev, Marjan
This article presents the activities and the mechanisms of scanning the effectiveness of e-Government services in Republic of North Macedonia. The goal is to compare the results with other European Union members and Western Balkan’s countries. The used methodology for scanning the effectiveness of e-Government services is adopted by the European Union, but since North Macedonia is not a member of the Union, the scanning was not conducted within their earlier measurement reports. These results will help the e-Government institutions in North Macedonia to set priorities and improve their services. Finally, the Government can sooner implement the proposed development standards and integrate in the European e-Government services framework, since the benchmark score is below EU average.

Faculty of Computer Science and Engineering

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