The adoption of transactional memory is hindered by the high overhead of software transactional memory and the intrusive design changes required by previously proposed TM hardware. We propose that hardware to accelerate software transactional memory (STM) can reside outside an unmodified commodity processor core, thereby substantially reducing implementation costs. This paper introduces Transactional Memory Acceleration using Commodity Cores (TMACC), a hardware-accelerated TM system that does not modify the processor, caches, or coherence protocol. We present a complete hardware implementation of TMACC using a rapid prototyping platform. Using this hardware, we implement two unique conflict detection schemes which are accelerated using Bloom filters on an FPGA. These schemes employ novel techniques for tolerating the latency of fine-grained asynchronous communication with an out-of-core accelerator. We then conduct experiments to explore the feasibility of accelerating TM without modifying existing system hardware. We show that, for all but short transactions, it is not necessary to modify the processor to obtain substantial improvement in TM performance. In these cases, TMACC outperforms an STM by an average of 69 % in applications using moderate-length transactions, showing maximum speedup within 8 % of an upper bound on TM acceleration. Overall, we demonstrate that hardware can substantially accelerate the performance of an STM on unmodified commodity processors.

This paper presents an interesting system-level co-design and co-verification case study for a non-trivial design where multiple high-performing x86 processors and custom hardware were connected through a coherent interconnection fabric. In functional verification of such a system, we used a processor bus functional model (BFM) to combine native software execution with a cycle-accurate interconnect simulator and an HDL simulator. However, we found that significant extensions need to be made to the conventional BFM methodology in order to capture various data-race cases in simulation, which eventually happen in modern multiprocessor systems. Especially essential were faithful implementations of the memory consistency model and cache coherence protocol, as well as timing randomization. We demonstrate how such a co-simulation environment can be constructed from existing tools and software. Lessons from our study can similarly be applied to design and verification of other tightly-coupled systems.

A prototyping environment for high performance reconfigurable computing