GPURepair: Automated Repair of GPU Kernels

This paper presents a tool for repairing errors in GPU kernels written in CUDA or OpenCL due to data races and barrier divergence. Our novel extension to prior work can also remove barriers that are deemed unnecessary for correctness. We implement these ideas in our tool called GPURepair, which uses GPUVerify as the verification oracle for GPU kernels. We also extend GPUVerify to support CUDA Cooperative Groups, allowing GPURepair to perform inter-block synchronization for CUDA kernels. To the best of our knowledge, GPURepair is the only tool that can propose a fix for intra-block data races and barrier divergence errors for both CUDA and OpenCL kernels and the only tool that fixes inter-block data races for CUDA kernels. We perform extensive experiments on about 750 kernels and provide a comparison with prior work. We demonstrate the superiority of GPURepair through its capability to fix more kernels and its unique ability to remove redundant barriers and handle inter-block data races.Comment: 19 pages, 1 algorithm, 3 figures, 22nd International Conference on Verification Model Checking and Abstract Interpretation (VMCAI 2021

Diagnostic value of coronary CT angiography with prospective ECG-gating in the diagnosis of coronary artery disease: a systematic review and meta-analysis

To perform a systematic review and meta-analysis of the diagnostic value of prospective ECG-gating coronary CT angiography in the diagnosis of coronary artery disease. A search of biomedical databases for English literature was performed to identify studies investigating the diagnostic value of 64- or more slice CT angiography with use of prospective ECG-gating in the diagnosis of coronary artery disease. Sensitivity, specificity, positive and negative predictive value estimates pooled across studies were tested using a fixed effects model. Fourteen studies met selection criteria for inclusion in the analysis. Pooled estimates and 95% confidence interval (CI) of sensitivity, specificity, positive and negative predictive value of prospective ECG-gating coronary CT angiography for diagnosis of significant coronary stenosis were 99% (95% CI: 98, 100%), 91% (95% CI: 88, 94%), 94% (95% CI: 91, 96%) and 99% (95% CI: 97, 100%), according to the patient-based assessment. The mean values of sensitivity, specificity, positive and negative predictive value of prospective ECG-gating coronary CT angiography were 95% (95% CI: 93, 96%), 95% (95% CI: 93, 95%), 88% (95% CI: 86, 90%), and 98% (95% CI: 97, 98%), according to vessel-based assessment; 92% (95% CI: 90, 93%), 97% (95% CI: 97, 98%), 84% (95% CI: 82, 86%), 99% (95% CI: 99, 99%), according to segment-based assessment, respectively. The mean effective dose was 3.3 mSv (95% CI: 2.3, 4.1 mSv) for the prospective ECG-gating coronary CT angiography. This analysis shows that for a predominantly male population with a high disease prevalence the use of coronary CT angiography with prospective ECG gating allows for a reduced radiation exposure without a sacrifice in diagnostic efficacy