Hardware and Multimedia Processing
Hardware layers that determine multimedia performance, from sensors and ADCs to CPUs, SIMD, GPUs, memory systems and embedded accelerators.
Multimedia performance depends on the complete hardware path from sensors to memory and accelerators, not only on the algorithm. The high data volume of image and audio workloads makes data movement as important as arithmetic throughput.
Acquisition hardware
Camera sensors and microphones convert physical signals into electrical data. ADC resolution, sampling rate, analogue-front-end noise and clock stability define important properties of the resulting digital stream.
CPU, SIMD and GPU
CPUs handle irregular control flow efficiently. SIMD performs the same operation across multiple pixels, samples or vector elements. GPU acceleration provides high throughput for massively parallel operations such as convolutions and matrix multiplication.
Acceleration cost also includes host-device transfer, kernel launch and synchronisation. For small workloads these overheads may dominate total runtime.
Memory and data movement
High-resolution frames and long audio buffers stress the memory system. Unnecessary copies, poor cache locality and repeated format conversion consume bandwidth without adding information.
Buffer reuse, appropriate data layout and zero-copy paths can provide larger gains than arithmetic optimisation in memory-bound pipelines.
Embedded and real-time systems
DSPs, FPGAs and NPUs can improve energy efficiency for selected workloads. Under strict deadlines, worst-case latency matters more than average throughput. Hardware selection should therefore consider memory bandwidth, transfer cost and determinism in addition to FLOPS.
