Software trace cache

We explore the use of compiler optimizations, which optimize the layout of instructions in memory. The target is to enable the code to make better use of the underlying hardware resources regardless of the specific details of the processor/architecture in order to increase fetch performance. The Software Trace Cache (STC) is a code layout algorithm with a broader target than previous layout optimizations. We target not only an improvement in the instruction cache hit rate, but also an increase in the effective fetch width of the fetch engine. The STC algorithm organizes basic blocks into chains trying to make sequentially executed basic blocks reside in consecutive memory positions, then maps the basic block chains in memory to minimize conflict misses in the important sections of the program. We evaluate and analyze in detail the impact of the STC, and code layout optimizations in general, on the three main aspects of fetch performance; the instruction cache hit rate, the effective fetch width, and the branch prediction accuracy. Our results show that layout optimized, codes have some special characteristics that make them more amenable for high-performance instruction fetch. They have a very high rate of not-taken branches and execute long chains of sequential instructions; also, they make very effective use of instruction cache lines, mapping only useful instructions which will execute close in time, increasing both spatial and temporal locality.Peer ReviewedPostprint (published version

Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling

Though the GPGPU concept is well-known in image processing, much more work remains to be done to fully exploit GPUs as an alternative computation engine. This paper investigates the computation-to-core mapping strategies to probe the efficiency and scalability of the robust facet image modeling algorithm on GPUs. Our fine-grained computation-to-core mapping scheme shows a significant performance gain over the standard pixel-wise mapping scheme. With in-depth performance comparisons across the two different mapping schemes, we analyze the impact of the level of parallelism on the GPU computation and suggest two principles for optimizing future image processing applications on the GPU platform

Virtual cluster scheduling through the scheduling graph

This paper presents an instruction scheduling and cluster assignment approach for clustered processors. The proposed technique makes use of a novel representation named the scheduling graph which describes all possible schedules. A powerful deduction process is applied to this graph, reducing at each step the set of possible schedules. In contrast to traditional list scheduling techniques, the proposed scheme tries to establish relations among instructions rather than assigning each instruction to a particular cycle. The main advantage is that wrong or poor schedules can be anticipated and discarded earlier. In addition, cluster assignment of instructions is performed using another novel concept called virtual clusters, which define sets of instructions that must execute in the same cluster. These clusters are managed during the deduction process to identify incompatibilities among instructions. The mapping of virtual to physical clusters is postponed until the scheduling of the instructions has finalized. The advantages this novel approach features include: (1) accurate scheduling information when assigning, and, (2) accurate information of the cluster assignment constraints imposed by scheduling decisions. We have implemented and evaluated the proposed scheme with superblocks extracted from Speclnt95 and MediaBench. The results show that this approach produces better schedules than the previous state-of-the-art. Speed-ups are up to 15%, with average speed-ups ranging from 2.5% (2-Clusters) to 9.5% (4-Clusters).Peer ReviewedPostprint (published version

Instruction fetch architectures and code layout optimizations

The design of higher performance processors has been following two major trends: increasing the pipeline depth to allow faster clock rates, and widening the pipeline to allow parallel execution of more instructions. Designing a higher performance processor implies balancing all the pipeline stages to ensure that overall performance is not dominated by any of them. This means that a faster execution engine also requires a faster fetch engine, to ensure that it is possible to read and decode enough instructions to keep the pipeline full and the functional units busy. This paper explores the challenges faced by the instruction fetch stage for a variety of processor designs, from early pipelined processors, to the more aggressive wide issue superscalars. We describe the different fetch engines proposed in the literature, the performance issues involved, and some of the proposed improvements. We also show how compiler techniques that optimize the layout of the code in memory can be used to improve the fetch performance of the different engines described Overall, we show how instruction fetch has evolved from fetching one instruction every few cycles, to fetching one instruction per cycle, to fetching a full basic block per cycle, to several basic blocks per cycle: the evolution of the mechanism surrounding the instruction cache, and the different compiler optimizations used to better employ these mechanisms.Peer ReviewedPostprint (published version

Description and Optimization of Abstract Machines in a Dialect of Prolog

In order to achieve competitive performance, abstract machines for Prolog and related languages end up being large and intricate, and incorporate sophisticated optimizations, both at the design and at the implementation levels. At the same time, efficiency considerations make it necessary to use low-level languages in their implementation. This makes them laborious to code, optimize, and, especially, maintain and extend. Writing the abstract machine (and ancillary code) in a higher-level language can help tame this inherent complexity. We show how the semantics of most basic components of an efficient virtual machine for Prolog can be described using (a variant of) Prolog. These descriptions are then compiled to C and assembled to build a complete bytecode emulator. Thanks to the high level of the language used and its closeness to Prolog, the abstract machine description can be manipulated using standard Prolog compilation and optimization techniques with relative ease. We also show how, by applying program transformations selectively, we obtain abstract machine implementations whose performance can match and even exceed that of state-of-the-art, highly-tuned, hand-crafted emulators.Comment: 56 pages, 46 figures, 5 tables, To appear in Theory and Practice of Logic Programming (TPLP

On-stack replacement, distilled

On-stack replacement (OSR) is essential technology for adaptive optimization, allowing changes to code actively executing in a managed runtime. The engineering aspects of OSR are well-known among VM architects, with several implementations available to date. However, OSR is yet to be explored as a general means to transfer execution between related program versions, which can pave the road to unprecedented applications that stretch beyond VMs. We aim at filling this gap with a constructive and provably correct OSR framework, allowing a class of general-purpose transformation functions to yield a special-purpose replacement. We describe and evaluate an implementation of our technique in LLVM. As a novel application of OSR, we present a feasibility study on debugging of optimized code, showing how our techniques can be used to fix variables holding incorrect values at breakpoints due to optimizations

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