International Parallel and Distributed Processing Symposium/International Parallel Processing Symposium, 1996
This paper presents an assessment of the applicability of the Mesh Synchronous Processor (MeshSP)... more This paper presents an assessment of the applicability of the Mesh Synchronous Processor (MeshSP) architecture to a class of radar signal processing algorithms known as space-time adaptive processing (STAP). The MeshSP is a SIMD processor developed at MIT Lincoln Laboratory and marketed by Integrated Computing Engines, Inc. A high-level overview of the MeshSP architecture is presented. Mappings of a matrix
13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2007), 2007
We consider a resource synthesis technique for realtime systems where dynamic voltage scaling is ... more We consider a resource synthesis technique for realtime systems where dynamic voltage scaling is supported, the energy budget is limited, and the performance of the system depends on how resources and energy are used. We propose a resource synthesis technique that derives both the supply voltages and the resource allocation of the tasks in the system to maximize system performance. The resulting system satisfies real-time schedulability and energy requirements.
Stream processing exploits the properties of stream applications such as parallelism and throughp... more Stream processing exploits the properties of stream applications such as parallelism and throughput-oriented nature of the applications. One of recent approaches is communityimplemented a High-Level Compiler that produces SVM output renderings and SVM implementation. The SVM is implemented with the Raw Compiler as the LLC and an accompanying library. We also implemented stream applications such as matrix multiplication, FIR bank, and Ground Moving Target Indicator (GMTI) using the implemented compilers. These applications are optimized and the results are analyzed. The results show that the SVM framework is generally suitable for streaming applications on Raw processor.
International Parallel and Distributed Processing Symposium/International Parallel Processing Symposium, 1996
This paper presents an assessment of the applicability of the Mesh Synchronous Processor (MeshSP)... more This paper presents an assessment of the applicability of the Mesh Synchronous Processor (MeshSP) architecture to a class of radar signal processing algorithms known as space-time adaptive processing (STAP). The MeshSP is a SIMD processor developed at MIT Lincoln Laboratory and marketed by Integrated Computing Engines, Inc. A high-level overview of the MeshSP architecture is presented. Mappings of a matrix
13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2007), 2007
We consider a resource synthesis technique for realtime systems where dynamic voltage scaling is ... more We consider a resource synthesis technique for realtime systems where dynamic voltage scaling is supported, the energy budget is limited, and the performance of the system depends on how resources and energy are used. We propose a resource synthesis technique that derives both the supply voltages and the resource allocation of the tasks in the system to maximize system performance. The resulting system satisfies real-time schedulability and energy requirements.
Stream processing exploits the properties of stream applications such as parallelism and throughp... more Stream processing exploits the properties of stream applications such as parallelism and throughput-oriented nature of the applications. One of recent approaches is communityimplemented a High-Level Compiler that produces SVM output renderings and SVM implementation. The SVM is implemented with the Raw Compiler as the LLC and an accompanying library. We also implemented stream applications such as matrix multiplication, FIR bank, and Ground Moving Target Indicator (GMTI) using the implemented compilers. These applications are optimized and the results are analyzed. The results show that the SVM framework is generally suitable for streaming applications on Raw processor.
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Papers by Janice Mcmahon