Research on rapid development platform of PLC control system

In the field of industrial process control,a fast-development platform for programmable logic controller(PLC)systems is designed in order to solve two main problems of rapid development of PLC control system and programmability of controlling software.In the aspect of design,the platform is composed of hardware controlling and software monitoring and is taking industrial computer as the core.Under the Windows environment,the platform establishes the control instruction set,develops the configuration function and visual programming function of the monitoring software and it integrates PLC controller based on Visual Basic software.In order to achieve the function of data monitoring,it has realized the serial communication between computer and PLC by using RS-485 and RS-232 serial ports line communication.The platform designs the intelligent instruction scheduling strategy by studying the encoding and decoding rules of the communication instruction set.It proposes a method for rapidly developing control programs by adopting the expert control mode,which enables clients to develop and modify programs conveniently by importing instructions in a non-coded manner.After experimental testing,the platform is proved successful achieving both the rapid development of PLC control system and the rapid modification of monitoring software.

Data Dependence Graph Directed Scheduling for Clustered VLIW Architectures

This paper presents an instruction scheduling and cluster assignment approach for clustered very long instruction words （VLIW） processors. The technique produces high performance code by simultaneously balancing instructions among clusters and minimizing the amount of inter-cluster data communications. The scheme is evaluated based on benchmarks extracted from UTDSP. Results show a significant speedup compared with previously used techniques with speed-ups of up to 44%, with average speed-ups ranging from 14% （2-cluster） to 18% （4-cluster）.

An Energy-Efficient Instruction Scheduler Design with Two-Level Shelving and Adaptive Banking

Mainstream processors implement the instruction scheduler using a monolithic CAM-based issue queue （IQ）, which consumes increasingly high energy as its size scales. In particular, its instruction wakeup logic accounts for a major portion of the consumed energy. Our study shows that instructions with 2 non-ready operands （called 2OP instructions） are in small percentage, but tend to spend long latencies in the IQ. They can be effectively shelved in a small RAM-based waiting instruction buffer （WIB） and steered into the IQ at appropriate time. With this two-level shelving ability, half of the CAM tag comparators are eliminated in the IQ, which significantly reduces the energy of wakeup operation. In addition, we propose an adaptive banking scheme to downsize the IQ and reduce the bit-width of tag comparators. Experiments indicate that for an 8-wide issue superscalar or SMT proeessor,the energy consumption of the instruction scheduler can be reduced by 67%. Furthermore, the new design has potentially faster scheduler clock speed while maintaining close IPC to the monolithic scheduler design. Compared with the previous work on eliminating tags through prediction, our design is superior in terms of both energy reduction and SMT support.

MADET-A Machine-Description Table Based Instruction Scheduler in TH-RISC for Exploiting Instruction Level Parallelism

This paper presents a parameterized instruction scheduling algorithm based on machine description table for TH-RISC system, having a (3-5) stages pipeline structure.It would provide considerable fiexibility for instruction scheduling, improving execution efficiency for rapidly upgrading RISC machines. Alld, using this instruction scheduler as a tool, the effect of several methods for solving instruction interlock problem has been analyzed. Finally, a high performance approach combining the hardware feasibility and software effectiveness for solving instruction interlock problem, the improvement of instruction level parallelism (ILP) and speed-up results are given.The algorithm complexity is O(n2).