Efficiently computing static single assignment form and the control dependence graph
ACM Transactions on Programming Languages and Systems (TOPLAS)
LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
Pin: building customized program analysis tools with dynamic instrumentation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
GViM: GPU-accelerated virtual machines
Proceedings of the 3rd ACM Workshop on System-level Virtualization for High Performance Computing
An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness
Proceedings of the 36th annual international symposium on Computer architecture
A characterization and analysis of PTX kernels
IISWC '09 Proceedings of the 2009 IEEE International Symposium on Workload Characterization (IISWC)
An integrated GPU power and performance model
Proceedings of the 37th annual international symposium on Computer architecture
Ocelot: a dynamic optimization framework for bulk-synchronous applications in heterogeneous systems
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
Caracal: dynamic translation of runtime environments for GPUs
Proceedings of the Fourth Workshop on General Purpose Processing on Graphics Processing Units
A quantitative performance analysis model for GPU architectures
HPCA '11 Proceedings of the 2011 IEEE 17th International Symposium on High Performance Computer Architecture
Caracal: dynamic translation of runtime environments for GPUs
Proceedings of the Fourth Workshop on General Purpose Processing on Graphics Processing Units
Shadowfax: scaling in heterogeneous cluster systems via GPGPU assemblies
Proceedings of the 5th international workshop on Virtualization technologies in distributed computing
Encapsulated synchronization and load-balance in heterogeneous programming
Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
Proceedings of Workshop on General Purpose Processing Using GPUs
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In this paper we present the design and implementation of a dynamic instrumentation infrastructure for PTX programs that procedurally transforms kernels and manages related data structures. We show how performing instrumentation within the GPU Ocelot dynamic compiler infrastructure provides unique capabilities not available to other profiling and instrumentation toolchains for GPU computing. We demonstrate the utility of this instrumentation capability with three example scenarios - (1) performing workload characterization accelerated by a GPU, (2) providing load imbalance information for use by a resource allocator, and (3) providing compute utilization feedback to be used online by a simulated process scheduler that might be found in a hypervisor. Additionally, we measure both (1) the compilation overheads of performing dynamic compilation and (2) the increases in runtimes when executing instrumented kernels. On average, compilation overheads due to instrumentation consisted of 69% of the time needed to parse a kernel module, in the case of the Parboil benchmark suite. Slowdowns for instrumenting each basic block ranged from 1.5x to 5.5x, with the largest slowdowns attributed to kernels with large numbers of short, compute-bound blocks.