TriCheck: Memory Model Verification at the Trisection of Software, Hardware, and ISA

Memory consistency models (MCMs) which govern inter-module interactions in a shared memory system, are a significant, yet often under-appreciated, aspect of system design. MCMs are defined at the various layers of the hardware-software stack, requiring thoroughly verified specifications, compilers, and implementations at the interfaces between layers. Current verification techniques evaluate segments of the system stack in isolation, such as proving compiler mappings from a high-level language (HLL) to an ISA or proving validity of a microarchitectural implementation of an ISA. This paper makes a case for full-stack MCM verification and provides a toolflow, TriCheck, capable of verifying that the HLL, compiler, ISA, and implementation collectively uphold MCM requirements. The work showcases TriCheck's ability to evaluate a proposed ISA MCM in order to ensure that each layer and each mapping is correct and complete. Specifically, we apply TriCheck to the open source RISC-V ISA, seeking to verify accurate, efficient, and legal compilations from C11. We uncover under-specifications and potential inefficiencies in the current RISC-V ISA documentation and identify possible solutions for each. As an example, we find that a RISC-V-compliant microarchitecture allows 144 outcomes forbidden by C11 to be observed out of 1,701 litmus tests examined. Overall, this paper demonstrates the necessity of full-stack verification for detecting MCM-related bugs in the hardware-software stack.Comment: Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating System

Accelerating sequential programs using FastFlow and self-offloading

FastFlow is a programming environment specifically targeting cache-coherent shared-memory multi-cores. FastFlow is implemented as a stack of C++ template libraries built on top of lock-free (fence-free) synchronization mechanisms. In this paper we present a further evolution of FastFlow enabling programmers to offload part of their workload on a dynamically created software accelerator running on unused CPUs. The offloaded function can be easily derived from pre-existing sequential code. We emphasize in particular the effective trade-off between human productivity and execution efficiency of the approach.Comment: 17 pages + cove

Memory performance of and-parallel prolog on shared-memory architectures

The goal of the RAP-WAM AND-parallel Prolog abstract architecture is to provide inference speeds significantly beyond those of sequential systems, while supporting Prolog semantics and preserving sequential performance and storage efficiency. This paper presents simulation results supporting these claims with special emphasis on memory performance on a two-level sharedmemory multiprocessor organization. Several solutions to the cache coherency problem are analyzed. It is shown that RAP-WAM offers good locality and storage efficiency and that it can effectively take advantage of broadcast caches. It is argued that speeds in excess of 2 ML IPS on real applications exhibiting medium parallelism can be attained with current technology

Clarifying and compiling C/C++ concurrency: from C++11 to POWER

The upcoming C and C++ revised standards add concurrency to the languages, for the first time, in the form of a subtle *relaxed memory model* (the *C++11 model*). This aims to permit compiler optimisation and to accommodate the differing relaxed-memory behaviours of mainstream multiprocessors, combining simple semantics for most code with high-performance *low-level atomics* for concurrency libraries. In this paper, we first establish two simpler but provably equivalent models for C++11, one for the full language and another for the subset without consume operations. Subsetting further to the fragment without low-level atomics, we identify a subtlety arising from atomic initialisation and prove that, under an additional condition, the model is equivalent to sequential consistency for race-free programs

Connected component identification and cluster update on GPU

Cluster identification tasks occur in a multitude of contexts in physics and engineering such as, for instance, cluster algorithms for simulating spin models, percolation simulations, segmentation problems in image processing, or network analysis. While it has been shown that graphics processing units (GPUs) can result in speedups of two to three orders of magnitude as compared to serial codes on CPUs for the case of local and thus naturally parallelized problems such as single-spin flip update simulations of spin models, the situation is considerably more complicated for the non-local problem of cluster or connected component identification. I discuss the suitability of different approaches of parallelization of cluster labeling and cluster update algorithms for calculations on GPU and compare to the performance of serial implementations.Comment: 15 pages, 14 figures, one table, submitted to PR

Solving multiprocessor drawbacks with kilo-instruction processors

Nowadays, a good multiprocessor system design has to deal with many drawbacks in order to achieve a good tradeoff between complexity and performance. For example, while solving problems like coherence and consistency is essential for correctness the way to solve processor stalls due to critical sections and synchronization points is desirable for performance. And none of these drawbacks has a straightforward solution. We show in our paper how the multi-checkpointing mechanism of the Kilo-Instruction Processors can be correctly leveraged in order to achieve a good complexity-effective multiprocessor design. Specifically, we describe a Kilo-Instruction Multiprocessor that transparently, i.e. without any software support, uses transaction-based memory updates. Our model simplifies the coherence and consistency hardware and gives the potential for easily applying different desirable speculative mechanisms to enhance performance when facing some synchronization constructs of current parallel applications.Postprint (published version