21,316 research outputs found
The use of field-programmable gate arrays for the hardware acceleration of design automation tasks
This paper investigates the possibility of using Field-Programmable Gate Arrays (FrâGAS) as
reconfigurable co-processors for workstations to produce moderate speedups for most tasks
in the design process, resulting in a worthwhile overall design process speedup at low cost
and allowing algorithm upgrades with no hardware modification. The use of FPGAS as hardware
accelerators is reviewed and then achievable speedups are predicted for logic simulation
and VLSI design rule checking tasks for various FPGA co-processor arrangements
Using FPGAs to prototype a self-timed floating point co-processor
Journal ArticleSelf- timed circuits offer advantages over their synchronously clocked counterparts in a number of situations. However, self-timed design techniques are not widely used at present for a variety of reasons. One reason for the lack of experimentation with self-timed systems is the lack of commercially available parts to support this style of design. Field programmable gate arrays (FPGAs) offer an excellent alternative for the rapid development of novel system designs provided suitable circuit structures can be implemented. This paper describes a self-timed floating point co-processor built using a combination of Actel Field Programmable Gate Arrays (FPGAs) and semi-custom CMOS chips. This co-processor implements IEEE standard single precision floating point operations on 32-bit values. The control is completely self-timed. Data moves between parts of the circuit according to local constraints only: there is no global clock or global control circuit
Empowering parallel computing with field programmable gate arrays
After more than 30 years, reconïŹgurable computing has grown from a concept to a mature ïŹeld of science and technology. The cornerstone of this evolution is the ïŹeld programmable gate array, a building block enabling the conïŹguration of a custom hardware architecture. The departure from static von Neumannlike architectures opens the way to eliminate the instruction overhead and to optimize the execution speed and power consumption. FPGAs now live in a growing ecosystem of development tools, enabling software programmers to map algorithms directly onto hardware. Applications abound in many directions, including data centers, IoT, AI, image processing and space exploration. The increasing success of FPGAs is largely due to an improved toolchain with solid high-level synthesis support as well as a better integration with processor and memory systems. On the other hand, long compile times and complex design exploration remain areas for improvement. In this paper we address the evolution of FPGAs towards advanced multi-functional accelerators, discuss different programming models and their HLS language implementations, as well as high-performance tuning of FPGAs integrated into a heterogeneous platform. We pinpoint fallacies and pitfalls, and identify opportunities for language enhancements and architectural reïŹnements
Electrically reconfigurable logic array
To compose the complicated systems using algorithmically specialized logic circuits or processors, one solution is to perform relational computations such as union, division and intersection directly on hardware. These relations can be pipelined efficiently on a network of processors having an array configuration. These processors can be designed and implemented with a few simple cells. In order to determine the state-of-the-art in Electrically Reconfigurable Logic Array (ERLA), a survey of the available programmable logic array (PLA) and the logic circuit elements used in such arrays was conducted. Based on this survey some recommendations are made for ERLA devices
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