This paper presents a study of the statistical characteristics and multiplexing of Variable-Bit-Rate (VBR) MPEG-coded video streams. Our results are based on 23 minutes of video obtained from the entertainment movie, The Wizard of Oz. The experimental setup which was used to capture, digitize, and compress the video stream is described. Although the study is conducted at the frame level (as opposed to the slice level), it is observed that the inter-frame correlation structure for the frame-size sequence involves complicated forms of pseudo-periodicity that are mainly affected by the compression pattern of the sequence. A simple model for an MPEG traflc source is developed in which frames are generated according to the compression pattern of the original captured video stream. The number of cells per frame is fitted by a lognormal distribution. Simulations are used t o study the performance of an ATM multiplexer for MPEG streams.
Modern FPGA devices, which include (multiple) processor core(s) as diffused IP on the silicon die, provide an excellent platform for developing custom multiprocessor systems-on-programmable chip (MPSoPC) architectures. As researchers are investigating new methods for migrating portions of applications into custom hardware circuits, it is also critical to develop new run-time service frameworks to support these capabilities. Hthreads (HybridThreads) is a multithreaded RTOS kernel for hybrid FPGA/CPU systems designed to meet this new growing need. A key capability of hthreads is the migration of thread management, synchronization primitives, and run-time scheduling services for both hardware and software threads into hardware. This paper describes the hthreads scheduler, a key component for controlling both software-resident threads (SW threads) and threads implemented in programmable logic (HW threads). Run-time analysis shows that the hthreads scheduler module helps in reducing unwanted system overhead and jitter when compared to historical software schedulers, while fielding scheduling requests from both hardware and software threads in parallel with application execution. Run time analysis shows the scheduler achieves constant time scheduling for up to 256 active threads with a total of 128 different priority levels, while using uniform APIs for threads requesting OS services from either side of the hardware/software boundary.
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