Information Technology-Portable Operating System Interface
Information Technology-Portable Operating System Interface
Writing Portable Applications that Dynamically Bind at Run Time to Reconfigurable Hardware
FCCM '07 Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Merge: a programming model for heterogeneous multi-core systems
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Efficient hardware code generation for FPGAs
ACM Transactions on Architecture and Code Optimization (TACO)
Task and Conduit Framework for Multi-core Systems
HPCMP-UGC '08 Proceedings of the 2008 DoD HPCMP Users Group Conference
Axel: a heterogeneous cluster with FPGAs and GPUs
Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays
Proceedings of the ACM SIGPLAN/SIGBED 2010 conference on Languages, compilers, and tools for embedded systems
FPGA Circuit Synthesis of Accelerator Data-Parallel Programs
FCCM '10 Proceedings of the 2010 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines
Ocelot: a dynamic optimization framework for bulk-synchronous applications in heterogeneous systems
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
StarPU: a unified platform for task scheduling on heterogeneous multicore architectures
Concurrency and Computation: Practice & Experience - Euro-Par 2009
Editorial: Special issue editorial: Accelerators for high-performance computing
Journal of Parallel and Distributed Computing
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Special Purpose Processors (SPPs), including Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs), are increasingly being used to accelerate scientific applications. VForce aims to aid application programmers in using such accelerators with minimal changes in user code. VForce is an extensible middleware framework that enables VSIPL++ (the Vector Signal Image Processing Library extension) programs to transparently use Special Purpose Processors (SPPs) while maintaining portability across platforms with and without SPP hardware. The framework is designed to maintain a VSIPL++-like environment and hide hardware-specific details from the application programmer while preserving performance and productivity. VForce focuses on the interface between application code and accelerator code. The same application code can run in software on a general purpose processor or take advantage of SPPs if they are available. VForce is unique in that it supports calls to both FPGAs and GPUs while requiring no changes in user code. Results on systems with NVIDIA Tesla GPUs and Xilinx FPGAs are presented. This paper describes VForce, illustrates its support for portability, and discusses lessons learned for providing support for different hardware configurations at run time. Key considerations involve global knowledge about the relationship between processing steps for defining application mapping, memory allocation, and task parallelism.