Separation logic for high-level synthesis

High-level synthesis (HLS) promises a significant shortening of the digital hardware design cycle by raising the abstraction level of the design entry to high-level languages such as C/C++. However, applications using dynamic, pointer-based data structures remain difficult to implement well, yet such constructs are widely used in software. Automated optimisations that leverage the memory bandwidth of dedicated hardware implementations by distributing the application data over separate on-chip memories and parallelise the implementation are often ineffective in the presence of dynamic data structures, due to the lack of an automated analysis that disambiguates pointer-based memory accesses. This thesis takes a step towards closing this gap. We explore recent advances in separation logic, a rigorous mathematical framework that enables formal reasoning about the memory access of heap-manipulating programs. We develop a static analysis that automatically splits heap-allocated data structures into provably disjoint regions. Our algorithm focuses on dynamic data structures accessed in loops and is accompanied by automated source-to-source transformations which enable loop parallelisation and physical memory partitioning by off-the-shelf HLS tools. We then extend the scope of our technique to pointer-based memory-intensive implementations that require access to an off-chip memory. The extended HLS design aid generates parallel on-chip multi-cache architectures. It uses the disjointness property of memory accesses to support non-overlapping memory regions by private caches. It also identifies regions which are shared after parallelisation and which are supported by parallel caches with a coherency mechanism and synchronisation, resulting in automatically specialised memory systems. We show up to 15x acceleration from heap partitioning, parallelisation and the insertion of the custom cache system in demonstrably practical applications.Open Acces

Optimizing SIMD execution in HW/SW co-designed processors

SIMD accelerators are ubiquitous in microprocessors from different computing domains. Their high compute power and hardware simplicity improve overall performance in an energy efficient manner. Moreover, their replicated functional units and simple control mechanism make them amenable to scaling to higher vector lengths. However, code generation for these accelerators has been a challenge from the days of their inception. Compilers generate vector code conservatively to ensure correctness. As a result they lose significant vectorization opportunities and fail to extract maximum benefits out of SIMD accelerators. This thesis proposes to vectorize the program binary at runtime in a speculative manner, in addition to the compile time static vectorization. There are different environments that support runtime profiling and optimization support required for dynamic vectorization, one of most prominent ones being: 1) Dynamic Binary Translators and Optimizers (DBTO) and 2) Hardware/Software (HW/SW) Co-designed Processors. HW/SW co-designed environment provides several advantages over DBTOs like transparent incorporations of new hardware features, binary compatibility, etc. Therefore, we use HW/SW co-designed environment to assess the potential of speculative dynamic vectorization. Furthermore, we analyze vector code generation for wider vector units and find out that even though SIMD accelerators are amenable to scaling from the hardware point of view, vector code generation at higher vector length is even more challenging. The two major factors impeding vectorization for wider SIMD units are: 1) Reduced dynamic instruction stream coverage for vectorization and 2) Large number of permutation instructions. To solve the first problem we propose Variable Length Vectorization that iteratively vectorizes for multiple vector lengths to improve dynamic instruction stream coverage. Secondly, to reduce the number of permutation instructions we propose Selective Writing that selectively writes to different parts of a vector register and avoids permutations. Finally, we tackle the problem of leakage energy in SIMD accelerators. Since SIMD accelerators consume significant amount of real estate on the chip, they become the principle source of leakage if not utilized judiciously. Power gating is one of the most widely used techniques to reduce leakage energy of functional units. However, power gating has its own energy and performance overhead associated with it. We propose to selectively devectorize the vector code when higher SIMD lanes are used intermittently. This selective devectorization keeps the higher SIMD lanes idle and power gated for maximum duration. Therefore, resulting in overall leakage energy reduction.Postprint (published version

Efficient memory-level parallelism extraction with decoupled strands

We present Outrider, an architecture for throughput-oriented processors that exploits intra-thread memory-level parallelism (MLP) to improve performance efficiency on highly threaded workloads. Outrider enables a single thread of execution to be presented to the architecture as multiple decoupled instruction streams, consisting of either memory accessing or memory consuming instructions. The key insight is that by decoupling the instruction streams, the processor pipeline can expose MLP in a way similar to out-of-order designs while relying on a low-complexity in-order micro-architecture. Instead of adding more threads as is done in modern GPUs, Outrider can expose the same MLP with fewer threads and reduced contention for resources shared among threads. We demonstrate that Outrider can outperform single-threaded cores by 23-131% and a 4-way simultaneous multi-threaded core by up to 87% in data parallel applications in a 1024-core system. Outrider achieves these performance gains without incurring the overhead of additional hardware thread contexts, which results in improved efficiency compared to a multi-threaded core

Percolation-based compiling for evaluation of parallelism and hardware design trade-offs

This thesis investigates parallelism and hardware design trade-offs of parallel and pipelined architectures. To explore these trade-offs we developed a retargetable compiler based on a set of powerful code transformations called Percolation Scheduling (PS) that map programs with real-time constraints and/or massive time requirements onto synchronous, parallel, high-performance or semi-custom architectures.High-performance is achieved through extraction of application inherent fine-grain parallelism and the use of a suitable architecture. Exploiting fine-grain parallelism is a critical part of exploiting all of the parallelism available in a given program, particularly since highly irregular forms of parallelism are often not visible at coarser levels and since the use of low-level parallelism has a multiplicative effect on the overall performance.To extract substantial parallelism from both the hardware and the compiler, we use a clean, highly parallel VLIW-like architecture that is synchronous, has multiple functional units and has a single program counter. The use of a hazard-free and homogeneous architecture does not result only in a better VLSI design but also considerably increases the compiler's ability to produce better code. To further enhance parallelism we modified the uni-cycle VLIW model and extended the transformations such that pipelined units that provide extra parallelism are used.Another approach presented is of resource constrained scheduling (RCS). Since the RCS problem is known to be NP-hard, in practice it may be solved only by a heuristic approach. We argue that using the heuristic after extraction of the unlimited-resources schedule may yield better results than if the heuristic has been applied at the beginning of the scheduling process.Through a series of benchmarks we evaluate hardware design trade-offs and show that speed-ups on average of one order of magnitude are feasible with sufficient functional units. However, when resources are limited we show that the number of functional units needed may be optimized for a particular suite of application programs

HW/SW mechanisms for instruction fusion, issue and commit in modern u-processors

In this thesis we have explored the co-designed paradigm to show alternative processor design points. Specifically, we have provided HW/SW mechanisms for instruction fusion, issue and commit for modern processors. We have implemented a co-designed virtual machine monitor that binary translates x86 instructions into RISC like micro-ops. Moreover, the translations are stored as superblocks, which are a trace of basic blocks. These superblocks are further optimized using speculative and non-speculative optimizations. Hardware mechanisms exists in-order to take corrective action in case of misspeculations. During the course of this PhD we have made following contributions. Firstly, we have provided a novel Programmable Functional unit, in-order to speed up general-purpose applications. The PFU consists of a grid of functional units, similar to CCA, and a distributed internal register file. The inputs of the macro-op are brought from the Physical Register File to the internal register file using a set of moves and a set of loads. A macro-op fusion algorithm fuses micro-ops at runtime. The fusion algorithm is based on a scheduling step that indicates whether the current fused instruction is beneficial or not. The micro-ops corresponding to the macro-ops are stored as control signals in a configuration. The macro-op consists of a configuration ID which helps in locating the configurations. A small configuration cache is present inside the Programmable Functional unit, that holds these configurations. In case of a miss in the configuration cache configurations are loaded from I-Cache. Moreover, in-order to support bulk commit of atomic superblocks that are larger than the ROB we have proposed a speculative commit mechanism. For this we have proposed a Speculative commit register map table that holds the mappings of the speculatively committed instructions. When all the instructions of the superblock have committed the speculative state is copied to Backend Register Rename Table. Secondly, we proposed a co-designed in-order processor with with two kinds of accelerators. These FU based accelerators run a pair of fused instructions. We have considered two kinds of instruction fusion. First, we fused a pair of independent loads together into vector loads and execute them on vector load units. For the second kind of instruction fusion we have fused a pair of dependent simple ALU instructions and execute them in Interlock Collapsing ALUs (ICALU). Moreover, we have evaluated performance of various code optimizations such as list-scheduling, load-store telescoping and load hoisting among others. We have compared our co-designed processor with small instruction window out-of-order processors. Thirdly, we have proposed a co-designed out-of-order processor. Specifically we have reduced complexity in two areas. First of all, we have co-designed the commit mechanism, that enable bulk commit of atomic superblocks. In this solution we got rid of the conventional ROB, instead we introduce the Superblock Ordering Buffer (SOB). SOB ensures program order is maintained at the granularity of the superblock, by bulk committing the program state. The program state consists of the register state and the memory state. The register state is held in a per superblock register map table, whereas the memory state is held in gated store buffer and updated in bulk. Furthermore, we have tackled the complexity of Out-of-Order issue logic by using FIFOs. We have proposed an enhanced steering heuristic that fixes the inefficiencies of the existing dependence-based heuristic. Moreover, a mechanism to release the FIFO entries earlier is also proposed that further improves the performance of the steering heuristic.En aquesta tesis hem explorat el paradigma de les màquines issue i commit per processadors actuals. Hem implementat una màquina virtual que tradueix binaris x86 a micro-ops de tipus RISC. Aquestes traduccions es guarden com a superblocks, que en realitat no és més que una traça de virtuals co-dissenyades. En particular, hem proposat mecanismes hw/sw per a la fusió d’instruccions, blocs bàsics. Aquests superblocks s’optimitzen utilitzant optimizacions especualtives i d’altres no speculatives. En cas de les optimizations especulatives es consideren mecanismes per a la gestió de errades en l’especulació. Al llarg d’aquesta tesis s’han fet les següents contribucions: Primer, hem proposat una nova unitat functional programmable (PFU) per tal de millorar l’execució d’aplicacions de proposit general. La PFU està formada per un conjunt d’unitats funcionals, similar al CCA, amb un banc de registres intern a la PFU distribuït a les unitats funcionals que la composen. Les entrades de la macro-operació que s’executa en la PFU es mouen del banc de registres físic convencional al intern fent servir un conjunt de moves i loads. Un algorisme de fusió combina més micro-operacions en temps d’execució. Aquest algorisme es basa en un pas de planificació que mesura el benefici de les decisions de fusió. Les micro operacions corresponents a la macro operació s’emmagatzemen com a senyals de control en una configuració. Les macro-operacions tenen associat un identificador de configuració que ajuda a localitzar d’aquestes. Una petita cache de configuracions està present dintre de la PFU per tal de guardar-les. En cas de que la configuració no estigui a la cache, les configuracions es carreguen de la cache d’instruccions. Per altre banda, per tal de donar support al commit atòmic dels superblocks que sobrepassen el tamany del ROB s’ha proposat un mecanisme de commit especulatiu. Per aquest mecanisme hem proposat una taula de mapeig especulativa dels registres, que es copia a la taula no especulativa quan totes les instruccions del superblock han comitejat. Segon, hem proposat un processador en order co-dissenyat que combina dos tipus d’acceleradors. Aquests acceleradors executen un parell d’instruccions fusionades. S’han considerat dos tipus de fusió d’instructions. Primer, combinem un parell de loads independents formant loads vectorials i els executem en una unitat vectorial. Segon, fusionem parells d’instruccions simples d’alu que són dependents i que s’executaran en una Interlock Collapsing ALU (ICALU). Per altra aquestes tecniques les hem evaluat conjuntament amb diverses optimizacions com list scheduling, load-store telescoping i hoisting de loads, entre d’altres. Aquesta proposta ha estat comparada amb un processador fora d’ordre. Tercer, hem proposat un processador fora d’ordre co-dissenyat efficient reduint-ne la complexitat en dos areas principals. En primer lloc, hem co-disenyat el mecanisme de commit per tal de permetre un eficient commit atòmic del superblocks. En aquesta solució hem substituït el ROB convencional, i en lloc hem introduït el Superblock Ordering Buffer (SOB). El SOB manté l’odre de programa a granularitat de superblock. L’estat del programa consisteix en registres i memòria. L’estat dels registres es manté en una taula per superblock, mentre que l’estat de memòria es guarda en un buffer i s’actulitza atòmicament. La segona gran area de reducció de complexitat considerarada és l’ús de FIFOs a la lògica d’issue. En aquest últim àmbit hem proposat una heurística de distribució que solventa les ineficiències de l’heurística basada en dependències anteriorment proposada. Finalment, i junt amb les FIFOs, s’ha proposat un mecanisme per alliberar les entrades de la FIFO anticipadament

HELIX-RC

Data dependences in sequential programs limit parallelization because extracted threads cannot run independently. Although thread-level speculation can avoid the need for precise dependence analysis, communication overheads required to synchronize actual dependences counteract the benefits of parallelization. To address these challenges, we propose a lightweight architectural enhancement co-designed with a parallelizing compiler, which together can decouple communication from thread execution. Simulations of these approaches, applied to a processor with 16 Intel Atom-like cores, show an average of 6.85x performance speedup for six SPEC CINT2000 benchmarksThis work was possible thanks to the sponsorship of the Royal Academy of Engineering, EPSRC and the National Science Foundation (award number IIS-0926148).This is the accepted manuscript. The final version is available from IEEE and ACM at http://dl.acm.org/citation.cfm?doid=2678373.2665705

Techniques for advancing value prediction

Sequential performance is still an issue in computing. While some prediction mechanisms such as branch prediction and prefetching have been widely adopted in modern, general-purpose microprocessors, others such as value prediction have not been accepted due to their high area and misprediction overheads. True data dependences form a major bottleneck in sequential performance and value prediction can be employed to speculatively resolve these dependences. Accurate predictors [1] [2] have been shown to provide performance benefits, albeit requiring a large predictor state. We argue that a first step in making value prediction practical is to manage the metadata associated with the predictor effectively. Inspired by irregular prefetchers that store their metadata in off-chip memory, we propose the use of an improved prefetching mechanism for value prediction that not only provides performance benefits but also a means to off-load predictor state to the memory hierarchy. We show an average of 5.3% IPC improvements across a set of Qualcomm-provided traces [3]. The result of a static instruction can be predicted by mapping runtime context information to the value produced by the instruction. To that end, existing value predictors either use branch history contexts [2] or value history contexts [1] to make predictions. As long histories are needed to achieve high accuracy, these approaches slow down the training time of the predictor, negatively impacting coverage. We identify that branch and value histories both provide distinct advantages to a value predictor, and therefore combine them in a novel predictor design called the Relevant Context-based Predictor (RCP) that maintains high accuracy while improving training time. We show an average of 38% speedup over a baseline that performs no value prediction on the Qualcomm-provided traces, compared to 34% by the previous best.Electrical and Computer Engineerin

Design of a distributed memory unit for clustered microarchitectures

Power constraints led to the end of exponential growth in single–processor performance, which characterized the semiconductor industry for many years. Single–chip multiprocessors allowed the performance growth to continue so far. Yet, Amdahl’s law asserts that the overall performance of future single–chip multiprocessors will depend crucially on single–processor performance. In a multiprocessor a small growth in single–processor performance can justify the use of significant resources. Partitioning the layout of critical components can improve the energy–efficiency and ultimately the performance of a single processor. In a clustered microarchitecture parts of these components form clusters. Instructions are processed locally in the clusters and benefit from the smaller size and complexity of the clusters components. Because the clusters together process a single instruction stream communications between clusters are necessary and introduce an additional cost. This thesis proposes the design of a distributed memory unit and first level cache in the context of a clustered microarchitecture. While the partitioning of other parts of the microarchitecture has been well studied the distribution of the memory unit and the cache has received comparatively little attention. The first proposal consists of a set of cache bank predictors. Eight different predictor designs are compared based on cost and accuracy. The second proposal is the distributed memory unit. The load and store queues are split into smaller queues for distributed disambiguation. The mapping of memory instructions to cache banks is delayed until addresses have been calculated. We show how disambiguation can be implemented efficiently with unordered queues. A bank predictor is used to map instructions that consume memory data near the data origin. We show that this organization significantly reduces both energy usage and latency. The third proposal introduces Dispatch Throttling and Pre-Access Queues. These mechanisms avoid load/store queue overflows that are a result of the late allocation of entries. The fourth proposal introduces Memory Issue Queues, which add functionality to select instructions for execution and re-execution to the memory unit. The fifth proposal introduces Conservative Deadlock Aware Entry Allocation. This mechanism is a deadlock safe issue policy for the Memory Issue Queues. Deadlocks can result from certain queue allocations because entries are allocated out-of-order instead of in-order like in traditional architectures. The sixth proposal is the Early Release of Load Queue Entries. Architectures with weak memory ordering such as Alpha, PowerPC or ARMv7 can take advantage of this mechanism to release load queue entries before the commit stage. Together, these proposals allow significantly smaller and more energy efficient load queues without the need of energy hungry recovery mechanisms and without performance penalties. Finally, we present a detailed study that compares the proposed distributed memory unit to a centralized memory unit and confirms its advantages of reduced energy usage and of improved performance

High level compilation for gate reconfigurable architectures

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 205-215).A continuing exponential increase in the number of programmable elements is turning management of gate-reconfigurable architectures as "glue logic" into an intractable problem; it is past time to raise this abstraction level. The physical hardware in gate-reconfigurable architectures is all low level - individual wires, bit-level functions, and single bit registers - hence one should look to the fetch-decode-execute machinery of traditional computers for higher level abstractions. Ordinary computers have machine-level architectural mechanisms that interpret instructions - instructions that are generated by a high-level compiler. Efficiently moving up to the next abstraction level requires leveraging these mechanisms without introducing the overhead of machine-level interpretation. In this dissertation, I solve this fundamental problem by specializing architectural mechanisms with respect to input programs. This solution is the key to efficient compilation of high-level programs to gate reconfigurable architectures. My approach to specialization includes several novel techniques. I develop, with others, extensive bitwidth analyses that apply to registers, pointers, and arrays. I use pointer analysis and memory disambiguation to target devices with blocks of embedded memory. My approach to memory parallelization generates a spatial hierarchy that enables easier-to-synthesize logic state machines with smaller circuits and no long wires.(cont.) My space-time scheduling approach integrates the techniques of high-level synthesis with the static routing concepts developed for single-chip multiprocessors. Using DeepC, a prototype compiler demonstrating my thesis, I compile a new benchmark suite to Xilinx Virtex FPGAs. Resulting performance is comparable to a custom MIPS processor, with smaller area (40 percent on average), higher evaluation speeds (2.4x), and lower energy (18x) and energy-delay (45x). Specialization of advanced mechanisms results in additional speedup, scaling with hardware area, at the expense of power. For comparison, I also target IBM's standard cell SA-27E process and the RAW microprocessor. Results include sensitivity analysis to the different mechanisms specialized and a grand comparison between alternate targets.by Jonathan William Babb.Ph.D