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Many scientific computations need multi-node parallelism for matching up bothspace (memory) and time (speed) ever-increasing requirements. The use of GPUsas accelerators introduces yet another level of complexity for the programmerand may potentially result in large overheads due to the complex memoryhierarchy. Additionally, top-notch problems may easily employ more than aPetaflops of sustained computing power, requiring thousands of GPUsorchestrated with some parallel programming model. Here we describe APEnet+,the new generation of our interconnect, which scales up to tens of thousands ofnodes with linear cost, thus improving the price/performance ratio on largeclusters. The project target is the development of the Apelink+ host adapterfeaturing a low latency, high bandwidth direct network, state-of-the-art wirespeeds on the links and a PCIe X8 gen2 host interface. It features hardwaresupport for the RDMA programming model and experimental acceleration of GPUnetworking. A Linux kernel driver, a set of low-level RDMA APIs and an OpenMPIlibrary driver are available, allowing for painless porting of standardapplications. Finally, we give an insight of future work and intendeddevelopments.

APEnet+: a 3D toroidal network enabling Petaflops scale Lattice QCD simulations on commodity clusters