Recent Trends in Parallel Computing

Edge computing brings computation closer to data sources, which supports low-latency applications but places substantial demands on energy-constrained and heterogeneous devices.

Linux control groups (cgroups) are the kernel mechanism that lets container runtimes such as Docker, containerd, and CRI-O enforce per-container CPU, memory, and I/O limits.

High-Performance Computing (HPC) has become an essential technology for solving computationally intensive problems in scientific computing, engineering, artificial intelligence, weather forecasting, computational biology, financial modelling, and large-scale data analytics.

Polyhedral compilation is a mathematically rigorous framework that models imperative loop nests as sets of integer points constrained by affine inequalities, enabling precise reasoning about data dependences and the legality of complex program transformations.

In the current EdTech sector, gathering structured data from various fragmented web portals is a major challenge for building reliable, real-time data systems.

The fast proliferation of large language models (LLMs) has increased the need to optimize the process of fine-tuning, but the existing workflows that require a graphics processing unit (GPU) are still expensive, intensive, and unavailable to most researchers.