We provide a case study of work-stealing, a popular method for run-time load balancing, on FPGAs. Following the Cederman-Tsigas implementation for GPUs, we synchronize workitems not with locks, mutexes or critical sections, but instead with the atomic operations provided by Altera's OpenCL SDK. We evaluate work-stealing for FPGAs by synthesizing a K-means clustering algorithm on an Altera P385 D5 board, both with work-stealing and with a statically-partitioned load. When block RAM utilization is maximized in both cases, we find that work-stealing leads to a 1.5× speedup. This demonstrates that the ability to do load balancing at run-time can outweigh the drawback of using 'expensive' atomics on FPGAs. We hope that our case study will stimulate further research into the high-level synthesis of fine-grained, lock-free, concurrent programs.
Lock-free algorithms, in which threads synchronise not via coarse-grained mutual exclusion but via fine-grained atomic operations ('atomics'), have been shown empirically to be the fastest class of multi-threaded algorithms in the realm of conventional processors. This paper explores how these algorithms can be compiled from C to reconfigurable hardware via high-level synthesis (HLS).We focus on the scheduling problem, in which software instructions are assigned to hardware clock cycles. We first show that typical HLS scheduling constraints are insufficient to implement atomics, because they permit some instruction reorderings that, though sound in a single-threaded context, demonstrably cause erroneous results when synthesising multi-threaded programs. We then show that correct behaviour can be restored by imposing additional intra-thread constraints among the memory operations. We implement our approach in the open-source LegUp HLS framework, and provide both sequentially consistent (SC) and weakly consistent ('weak') atomics. Weak atomics necessitate fewer constraints than SC atomics, but suffice for many concurrent algorithms. We confirm, via automatic model-checking, that we correctly implement the semantics defined by the 2011 revision of the C standard. A case study on a circular buffer suggests that circuits synthesised from programs that use atomics can be 2.5x faster than those that use locks, and that weak atomics can yield a further 1.5x speedup. Keywordsatomic operations, C/C++, FPGAs, high-level synthesis, lock-free algorithms, memory consistency models, scheduling.
Abstract-Lock-free algorithms, in which threads synchronise not via coarse-grained mutual exclusion but via fine-grained atomic operations ('atomics'), have been shown empirically to be the fastest class of multi-threaded algorithms in the realm of conventional processors. This article explores how these algorithms can be compiled from C to reconfigurable hardware via high-level synthesis (HLS).We focus on the scheduling problem, in which software instructions are assigned to hardware clock cycles. We first show that typical HLS scheduling constraints are insufficient to implement atomics, because they permit some instruction reorderings that, though sound in a single-threaded context, demonstrably cause erroneous results when synthesising multithreaded programs. We then show that correct behaviour can be restored by imposing additional intra-thread constraints among the memory operations. In addition, we show that we can support the pipelining of loops containing atomics by injecting further inter-iteration constraints. We implement our approach on two constraint-based scheduling HLS tools: LegUp 4.0 and LegUp 5.1. We extend both tools to support two memory models that are capable of synthesising atomics correctly. The first memory model only supports sequentially consistent (SC) atomics and the second supports weakly consistent ('weak') atomics as defined by the 2011 revision of the C standard. Weak atomics necessitate fewer constraints than SC atomics, but suffice for many multithreaded algorithms. We confirm, via automatic model-checking, that we correctly implement the semantics in accordance with the C standard. A case study on a circular buffer suggests that on average circuits synthesised from programs that schedule atomics correctly can be 6x faster than an existing lock-based implementation of atomics, that weak atomics can yield a further 1.3x speedup, and that pipelining can yield a further 1.3x speedup.
High-level synthesis (HLS), which refers to the automatic compilation of software into hardware, is rapidly gaining popularity. In a world increasingly reliant on application-specific hardware accelerators, HLS promises hardware designs of comparable performance and energy efficiency to those coded by hand in a hardware description language such as Verilog, while maintaining the convenience and the rich ecosystem of software development. However, current HLS tools cannot always guarantee that the hardware designs they produce are equivalent to the software they were given, thus undermining any reasoning conducted at the software level. Furthermore, there is mounting evidence that existing HLS tools are quite unreliable, sometimes generating wrong hardware or crashing when given valid inputs. To address this problem, we present the first HLS tool that is mechanically verified to preserve the behaviour of its input software. Our tool, called Vericert, extends the CompCert verified C compiler with a new hardware-oriented intermediate language and a Verilog back end, and has been proven correct in Coq. Vericert supports most C constructs, including all integer operations, function calls, local arrays, structs, unions, and general control-flow statements. An evaluation on the PolyBench/C benchmark suite indicates that Vericert generates hardware that is around an order of magnitude slower (only around 2× slower in the absence of division) and about the same size as hardware generated by an existing, optimising (but unverified) HLS tool.
When mapping C programs to hardware, high-level synthesis (HLS) tools seek to reorder instructions so they can be packed into as few clock cycles as possible. However, when synthesising multi-threaded C, instruction reordering is inhibited by the presence of atomic operations ('atomics'), such as compareand-swap. Atomics, the fundamental concurrency primitive in C, are the basis of more abstract concurrency mechanisms such as locks, and also of efficient lock-free data structures. Whether a particular atomic can be legally reordered within a thread can depend on the memory access patterns of other threads. Existing HLS tools that support atomics typically schedule each thread independently, and so must be conservative when optimising around atomics. Yet HLS tools are distinguished from conventional compilers by having the entire program available. Can this information be exploited to allow more reorderings within each thread, and hence to obtain more efficient schedules? In this work, we propose a global analysis that determines, for each thread, which pairs of instructions must not be reordered. Our analysis is sensitive to the C consistency mode of the atomics involved (e.g. relaxed, release, acquire, and sequentiallyconsistent). We have used the Alloy model checker to validate our analysis against the C language standard, and have implemented it in the LegUp HLS tool. An evaluation on several lock-free data structure benchmarks indicates that our analysis leads to a 1.6× average global speedup.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.