Late allocation and early release of physical registers

The register file is one of the critical components of current processors in terms of access time and power consumption. Among other things, the potential to exploit instruction-level parallelism is closely related to the size and number of ports of the register file. In conventional register renaming schemes, both register allocation and releasing are conservatively done, the former at the rename stage, before registers are loaded with values, and the latter at the commit stage of the instruction redefining the same register, once registers are not used any more. We introduce VP-LAER, a renaming scheme that allocates registers later and releases them earlier than conventional schemes. Specifically, physical registers are allocated at the end of the execution stage and released as soon as the processor realizes that there will be no further use of them. VP-LAER enhances register utilization, that is, the fraction of allocated registers having a value to be read in the future. Detailed cycle-level simulations show either a significant speedup for a given register file size or a reduction in the register file size for a given performance level, especially for floating-point codes, where the register file pressure is usually high.Peer ReviewedPostprint (published version

Near-optimal Assembly for Shotgun Sequencing with Noisy Reads

Recent work identified the fundamental limits on the information requirements in terms of read length and coverage depth required for successful de novo genome reconstruction from shotgun sequencing data, based on the idealistic assumption of no errors in the reads (noiseless reads). In this work, we show that even when there is noise in the reads, one can successfully reconstruct with information requirements close to the noiseless fundamental limit. A new assembly algorithm, X-phased Multibridging, is designed based on a probabilistic model of the genome. It is shown through analysis to perform well on the model, and through simulations to perform well on real genomes

A Minimalist Approach to Type-Agnostic Detection of Quadrics in Point Clouds

This paper proposes a segmentation-free, automatic and efficient procedure to detect general geometric quadric forms in point clouds, where clutter and occlusions are inevitable. Our everyday world is dominated by man-made objects which are designed using 3D primitives (such as planes, cones, spheres, cylinders, etc.). These objects are also omnipresent in industrial environments. This gives rise to the possibility of abstracting 3D scenes through primitives, thereby positions these geometric forms as an integral part of perception and high level 3D scene understanding. As opposed to state-of-the-art, where a tailored algorithm treats each primitive type separately, we propose to encapsulate all types in a single robust detection procedure. At the center of our approach lies a closed form 3D quadric fit, operating in both primal & dual spaces and requiring as low as 4 oriented-points. Around this fit, we design a novel, local null-space voting strategy to reduce the 4-point case to 3. Voting is coupled with the famous RANSAC and makes our algorithm orders of magnitude faster than its conventional counterparts. This is the first method capable of performing a generic cross-type multi-object primitive detection in difficult scenes. Results on synthetic and real datasets support the validity of our method.Comment: Accepted for publication at CVPR 201