Makespan computation for GPU threads running on a single streaming multiprocessor

Graphics processors were originally developed for rendering graphics but have recently evolved towards being an architecture for general-purpose computations. They are also expected to become important parts of embedded systems hardware -- not just for graphics. However, this necessitates the development of appropriate timing analysis techniques which would be required because techniques developed for CPU scheduling are not applicable. The reason is that we are not interested in how long it takes for any given GPU thread to complete, but rather how long it takes for all of them to complete. We therefore develop a simple method for finding an upper bound on the makespan of a group of GPU threads executing the same program and competing for the resources of a single streaming multiprocessor (whose architecture is based on NVIDIA Fermi, with some simplifying assunptions). We then build upon this method to formulate the derivation of the exact worst-case makespan (and corresponding schedule) as an optimization problem. Addressing the issue of tractability, we also present a technique for efficiently computing a safe estimate of the worstcase makespan with minimal pessimism, which may be used when finding an exact value would take too long.FCOMP-01-0124-FEDER-020447National Funds through the FCT-MCTES (Portuguese Foundation for Science and Technology) and by ERDF (European Regional Development Fund) through COMPETE (Operational Programme ‘Thematic Factors of Competitiveness’

Measurement-Based Probabilistic Timing Analysis for Graphics Processor Units

Architecture of Computing Systems (ARCS 2016). 4 to 7, Apr, 2016. Nuremberg, Germany.Purely analytical worst-case execution time (WCET) estimation approaches for Graphics Processor Units (GPUs) cannot go far because of insufficient public information for the hardware. Therefore measurement-based probabilistic timing analysis (MBPTA) seems the way forward. We recently demonstrated MBPTA for GPUs, based on Extreme Value Theory (EVT) of the “Block Maxima” paradigm. In this newer work, we formulate and experimentally evaluate a more robust MBPTA approach based on the EVT “Peak over Threshold” paradigm with a complete set of tests for verifying EVT applicability. It optimally selects parameters to best-fit the input measurements for more accurate probabilistic WCET estimates. Different system configuration parameters (cache arrangements, thread block size) and their effect on the pWCET are considered, enhancing models of worst-case GPU behavior.info:eu-repo/semantics/publishedVersio

Measurement-Based Probabilistic Timing Analysis for Graphics Pro cessor Units Kostiantyn Berezovskyi Measurement-Based Probabilistic Timing Analysis for Measurement-Based Probabilistic Timing Analysis for Graphics Pro cessor Units Measurement-Based Probab

Abstract Purely analytical worst-case execution time (WCET) estimation approaches for Graphics Processor Units (GPUs) cannot go farbecause of insufficient public information for the hardware. Thereforemeasurement-based probabilistic timing analysis (MBPTA) seems theway forward. We recently demonstrated MBPTA for GPUs, based onExtreme Value Theory (EVT) of the "Block Maxima" paradigm. In thisnewer work, we formulate and experimentally evaluate a more robustMBPTA approach based on the EVT "Peak over Threshold" paradigmwith a complete set of tests for verifying EVT applicability. It optimallyselects parameters to best-fit the input measurements for more accurateprobabilistic WCET estimates. Different system configuration parameters (cache arrangements, thread block size) and their effect on thepWCET are considered, enhancing models of worst-case GPU behavior. Measurement-Based Probabilistic Timing Analysis for Graphics Processor Units Abstract. Purely analytical worst-case execution time (WCET) estimation approaches for Graphics Processor Units (GPUs) cannot go far because of insufficient public information for the hardware. Therefore measurement-based probabilistic timing analysis (MBPTA) seems the way forward. We recently demonstrated MBPTA for GPUs, based on Extreme Value Theory (EVT) of the "Block Maxima" paradigm. In this newer work, we formulate and experimentally evaluate a more robust MBPTA approach based on the EVT "Peak over Threshold" paradigm with a complete set of tests for verifying EVT applicability. It optimally selects parameters to best-fit the input measurements for more accurate probabilistic WCET estimates. Different system configuration parameters (cache arrangements, thread block size) and their effect on the pWCET are considered, enhancing models of worst-case GPU behavior

Measurement-Based Probabilistic Timing Analysis for Graphics Processor Units

Architecture of Computing Systems (ARCS 2016). 4 to 7, Apr, 2016. Nuremberg, Germany.Purely analytical worst-case execution time (WCET) estimation approaches for Graphics Processor Units (GPUs) cannot go far because of insufficient public information for the hardware. Therefore measurement-based probabilistic timing analysis (MBPTA) seems the way forward. We recently demonstrated MBPTA for GPUs, based on Extreme Value Theory (EVT) of the “Block Maxima” paradigm. In this newer work, we formulate and experimentally evaluate a more robust MBPTA approach based on the EVT “Peak over Threshold” paradigm with a complete set of tests for verifying EVT applicability. It optimally selects parameters to best-fit the input measurements for more accurate probabilistic WCET estimates. Different system configuration parameters (cache arrangements, thread block size) and their effect on the pWCET are considered, enhancing models of worst-case GPU behavior.info:eu-repo/semantics/publishedVersio