Molecular dynamics (MD) simulation, a computationally intensive method that provides invaluable insights into the behavior of biomolecules, typically requires large-scale parallelization. Implementation of fast parallel MD simulation demands both high bandwidth and low latency for inter-node communication, but in current semiconductor technology, neither of these properties is scaling as quickly as intra-node computational capacity. This disparity in scaling necessitates architectural innovations to maximize the utilization of computational units. For Anton 3, the latest in a family of highly successful special-purpose supercomputers designed for MD simulations, we thus designed and built a completely new specialized network as part of our ASIC. Tightly integrating this network with specialized computation pipelines enables Anton 3 to perform simulations orders of magnitude faster than any general-purpose supercomputer, and to outperform its predecessor, Anton 2 (the state of the art prior to Anton 3), by an order of magnitude. In this paper, we present the three key features of the network that contribute to the high performance of Anton 3. First, through architectural optimizations, the network achieves very low end-to-end inter-node communication latency for fine-grained messages, allowing for better overlap of computation and communication. Second, novel application-specific compression techniques reduce the size of most messages sent between nodes, thereby increasing effective inter-node bandwidth. Lastly, a new hardware synchronization primitive, called a network fence, supports fast fine-grained synchronization tailored to the data flow within a parallel MD application. These application-driven specializations to the network are critical for Anton 3’s MD simulation performance advantage over all other machines.

• Understand biomolecular systems through their motions •Numerical integration of Newton's laws of motion — Model atoms as point masses — Compute forces on every atom based on current positions — Update atom velocities and positions in discrete time steps of a few femtoseconds • Force computation described by a model: the force field

Anton 3 is the newest member in a family of supercomputers specially designed for atomic-level simulation of molecules relevant to biology (e.g., DNA, proteins, and drug molecules). Anton 3 achieves order-of-magnitude improvements in time-to-solution over its predecessor, Anton 2 (the current state of the art), and is over 100-fold faster than any other currently available supercomputer, thereby enabling broad new avenues of research on critical questions in biology and drug discovery. This speedup means that a 512-node Anton 3 simulates a million atoms at over 100 microseconds per day. Furthermore, Anton 3 attains this performance while consuming an order of magnitude less energy per simulated microsecond than any other machine. Like its predecessors, Anton 3 was designed from the ground up around a new custom chip to best exploit the capabilities offered by new technologies. We present here the main architectural and algorithmic developments that were necessary to achieve such significant advances.

Organizations need to have undertaken an analysis of business risk and to have formulated a recovery plan. However, only a small number of businesses have made any attempt to minimize their risks and even fewer have a recovery plan which has been tested. Most are a token gesture to auditors. An out‐of‐date, untested plan can often be more dangerous than not having a plan at all as it lulls the organization into a false sense of security. But how do you test plans? If the strategy is to use a computer‐processing facility in another place – perhaps a commercial hot and cold site – the costs of regular testing can be high and the disruption to the business great. In tight economic times, senior management is too often prepared to gamble with the organization′s future. Develops a testing methodology, based on many years of designing plans and hands‐on testing, which reduces costs by breaking down the test procedure into components, modules and full tests.

Concentrates on the preparation for and the procedures to be followed in creating a disaster recovery plan. The recovery strategy, recovery teams, procedures and action tests, and maintenance and testing are all discussed in some detail.