HALO: Post-Link Heap-Layout Optimisation

Today, general-purpose memory allocators dominate the landscape of dynamic memory management. While these so- lutions can provide reasonably good behaviour across a wide range of workloads, it is an unfortunate reality that their behaviour for any particular workload can be highly suboptimal. By catering primarily to average and worst-case usage patterns, these allocators deny programs the advantages of domain-specific optimisations, and thus may inadvertently place data in a manner that hinders performance, generating unnecessary cache misses and load stalls. To help alleviate these issues, we propose HALO: a post-link profile-guided optimisation tool that can improve the layout of heap data to reduce cache misses automatically. Profiling the target binary to understand how allocations made in different contexts are related, we specialise memory-management routines to allocate groups of related objects from separate pools to increase their spatial locality. Unlike other solutions of its kind, HALO employs novel grouping and identification algorithms which allow it to create tight-knit allocation groups using the entire call stack and to identify these efficiently at runtime. Evaluation of HALO on contemporary out-of-order hardware demonstrates speedups of up to 28% over jemalloc, out-performing a state-of-the-art data placement technique from the literature

Resummed event-shape variables in DIS

We complete our study of resummed event-shape distributions in DIS by presenting results for the class of observables that includes the current jet mass, the C-parameter and the thrust with respect to the current-hemisphere thrust axis. We then compare our results to data for all observables for which data exist, fitting for alpha_s and testing the universality of non-perturbative 1/Q effects. A number of technical issues arise, including the extension of the concept of non-globalness to the case of discontinuous globalness; singularities and non-convergence of distributions other than in the Born limit; methods to speed up fixed-order Monte Carlo programs by up to an order of magnitude, relevant when dealing with many x and Q points; and the estimation of uncertainties on the predictions.Comment: 41 page