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.

Parallel implementations of molecular dynamics (MD) simulation require significant inter-node communication, but off-chip communication bandwidth is not scaling as quickly as on-chip logic density. We present three network features targeting this problem that have been implemented in Anton 2, a massively parallel special-purpose supercomputer for MD simulations. The first is a mechanism to dynamically identify packets that do not need to be delivered to all endpoints within a multicast tree, these packets are filtered to conserve network bandwidth. The second is hardware for in-network reductions that supports over a thousand concurrent neighbourhood reductions per node and fast all-to-all global reductions. The third is a log-weight synchronization mechanism for multicast-reduce communication patterns that can be used to efficiently detect the completion of reduction operations when the number of summands is difficult to predict. We use the combination of packet filtering, in-network reductions and log-weight synchronization to decrease the communication requirements of MD simulations by as much as 51% on Anton 2, yielding application-level performance improvements of up to 14%.

The design of network architectures has become increasingly complex as the chips connected by inter-node networks have emerged as distributed systems in their own right, complete with their own on-chip networks. In Anton 2, a massively parallel special-purpose supercomputer for molecular dynamics simulations, we managed this complexity by reusing the on-chip network as a switch for inter-node traffic. This unified network approach introduces several design challenges. Maintaining fairness within the inter-node network is difficult, as each hop becomes a sequence of many on-chip routing decisions. We addressed this problem with an inverse-weighted arbiter that ensures fairness with low implementation costs. Balancing the load of inter-node traffic across the on-chip network is also critical, and we adopted an optimization approach to design an appropriate routing algorithm. Finally, the on-chip routers carry inter-node traffic, so they must implement inter-node virtual channels to avoid deadlock. In order to keep the routers small and fast, we developed a deadlock-free routing algorithm that reduces the number of virtual channels by one-third relative to previous approaches. The resulting Anton 2 network implementation efficiently utilizes its inter-node channels and provides low messaging latency, while occupying a modest amount of silicon area.

Anton 2 is a second-generation special-purpose supercomputer for molecular dynamics simulations that achieves significant gains in performance, programmability, and capacity compared to its predecessor, Anton 1. The architecture of Anton 2 is tailored for fine-grained event-driven operation, which improves performance by increasing the overlap of computation with communication, and also allows a wider range of algorithms to run efficiently, enabling many new software-based optimizations. A 512-node Anton 2 machine, currently in operation, is up to ten times faster than Anton 1 with the same number of nodes, greatly expanding the reach of all-atom bio molecular simulations. Anton 2 is the first platform to achieve simulation rates of multiple microseconds of physical time per day for systems with millions of atoms. Demonstrating strong scaling, the machine simulates a standard 23,558-atom benchmark system at a rate of 85 μs/day -- 180 times faster than any commodity hardware platform or general-purpose supercomputer.

Exploiting parallelism to accelerate a computation typically involves dividing it into many small tasks that can be assigned to different processing elements. An efficient execution schedule for these tasks can be difficult or impossible to determine in advance, however, if there is uncertainty as to when each task's input data will be available. Ideally, each task would run in direct response to the arrival of its input data, thus allowing the computation to proceed in a fine-grained event-driven manner. Realizing this ideal is difficult in practice, and typically requires sacrificing flexibility for performance.

Cascade is a cycle-based C++ simulation infrastructure used in the design and verification of two successive versions of Anton, a specialized machine designed for high-speed molecular dynamics computation. Cascade was engineered to address the size and speed challenges inherent in simulating massively parallel special-purpose machines. It provides a lightweight programming interface, rich debugging support, tight Verilog integration, fast multithreaded execution, and low memory overhead. Here, we describe the core features of Cascade that proved most valuable for our simulation efforts.

Special-purpose computing hardware can provide significantly better performance and power efficiency for certain applications than general-purpose processors. Even within a single application area, however, a special-purpose machine can be far more valuable if it is capable of efficiently supporting a number of different computational methods that, taken together, expand the machine's functionality and range of applicability. We have previously described a massively parallel special-purpose supercomputer, called Anton, and have shown that it executes traditional molecular dynamics simulations orders of magnitude faster than the previous state of the art. Here, we describe how we extended Anton's software to support a more diverse set of methods, allowing scientists to simulate a broader class of biological phenomena at extremely high speeds. Key elements of our approach, which exploits Anton's tightly integrated hardwired pipelines and programmable cores, are applicable to the hardware and software design of various other specialized or heterogeneous parallel computing platforms.

Strong scaling of scientific applications on parallel architectures is increasingly limited by communication latency. This paper describes the techniques used to mitigate latency in Anton, a massively parallel special-purpose machine that accelerates molecular dynamics (MD) simulations by orders of magnitude compared with the previous state of the art. Achieving this speedup required a combination of hardware mechanisms and software constructs to reduce network latency, sender and receiver overhead, and synchronization costs. Key elements of Anton's approach, in addition to tightly integrated communication hardware, include formulating data transfer in terms of counted remote writes, leveraging fine-grained communication, and establishing fixed, optimized communication patterns. Anton delivers software-to-software inter-node latency significantly lower than any other large-scale parallel machine, and the total critical-path communication time for an Anton MD simulation is less than 4% that of the next fastest MD platform.

Anton is a recently completed special-purpose supercomputer designed for molecular dynamics (MD) simulations of biomolecular systems. The machine's specialized hardware dramatically increases the speed of MD calculations, making possible for the first time the simulation of biological molecules at an atomic level of detail for periods on the order of a millisecond---about two orders of magnitude beyond the previous state of the art. Anton is now running simulations on a timescale at which many critically important, but poorly understood phenomena are known to occur, allowing the observation of aspects of protein dynamics that were previously inaccessible to both computational and experimental study. Here, we report Anton's performance when executing actual MD simulations whose accuracy has been validated against both existing MD software and experimental observations. We also discuss the manner in which novel algorithms have been coordinated with Anton's co-designed, application-specific hardware to achieve these results.

Anton is a recently completed special-purpose supercomputer designed for molecular dynamics (MD) simulations of biomolecular systems. The machine's specialized hardware dramatically increases the speed of MD calculations, making possible for the first time the simulation of biological molecules at an atomic level of detail for periods on the order of a millisecond---about two orders of magnitude beyond the previous state of the art. Anton is now running simulations on a timescale at which many critically important, but poorly understood phenomena are known to occur, allowing the observation of aspects of protein dynamics that were previously inaccessible to both computational and experimental study. Here, we report Anton's performance when executing actual MD simulations whose accuracy has been validated against both existing MD software and experimental observations. We also discuss the manner in which novel algorithms have been coordinated with Anton's co-designed, application-specific hardware to achieve these results.

Anton, a massively parallel special-purpose machine for molecular dynamics simulations, performs a 32x32x32 FFT in 3.7 microseconds and a 64x64x64 FFT in 13.3 microseconds on a configuration with 512 nodes---an order of magnitude faster than all other FFT implementations of which we are aware. Achieving this FFT performance requires a coordinated combination of computation and communication techniques that leverage Anton's underlying hardware mechanisms. Most significantly, Anton's communication subsystem provides over 300 gigabits per second of bandwidth per node, message latency in the hundreds of nanoseconds, and support for word-level writes and single-ended communication. In addition, Anton's general-purpose computation system incorporates primitives that support the efficient parallelization of small 1D FFTs. Although Anton was designed specifically for molecular dynamics simulations, a number of the hardware primitives and software implementation techniques described in this paper may also be applicable to the acceleration of FFTs on general-purpose high-performance machines.

An effective special-purpose supercomputer for molecular dynamics (MD) requires much more than high-performance acceleration of computational kernels: such accelerators must be balanced with general-purpose computation and communication resources. Achieving this balance was a significant challenge in the design of Anton, a parallel machine that will accelerate MD simulations by several orders of magnitude. Anton executes its most computationally demanding calculations on a highly specialized, enormously parallel, but largely non-programmable high-throughput interaction subsystem (HTIS). Other elements of the simulation have a less uniform algorithmic structure, and may also change in response to future advances in physical models and simulation techniques. Such calculations are executed on Antonpsilas flexible subsystem, which combines programmability with the computational power required to avoid ldquoAmdahlpsilas Lawrdquo bottlenecks arising from the extremely high throughput of the HTIS. Antonpsilas flexible subsystem is a heterogeneous multiprocessor with 12 cores, each organized around a 128-bit data path. This subsystem includes hardware support for synchronization, data transfer and certain types of particle interactions, along with specialized instructions for geometric operations. All aspects of the flexible subsystem were designed specifically to accelerate MD simulations, and although it relies primarily on what may be regarded as ldquogeneral-purposerdquo processors, even this subsystem contains more application-specific features than many recently proposed ldquospecializedrdquo architectures.

Anton is a massively parallel special-purpose supercomputer designed to accelerate molecular dynamics (MD) simulations by several orders of magnitude, making possible for the first time the atomic-level simulation of many biologically important phenomena that take place over microsecond to millisecond time scales. The majority of the computation required for MD simulations involves the calculation of pairwise interactions between particles and/or gridpoints separated by no more than some specified cutoff radius. In Anton, such range-limited interactions are handled by a high-throughput interaction subsystem (HTIS). The HTIS on each of Antonpsilas 512 ASICs includes 32 computational pipelines running at 800 MHz, each producing a result on every cycle that would require approximately 50 arithmetic operations to compute on a general-purpose processor. In order to feed these pipelines and collect their results at a speed sufficient to take advantage of this computational power, Anton uses two novel techniques to limit inter- and intra-chip communication. The first is a recently developed parallelization algorithm for the range-limited N-body problem that offers major advantages in both asymptotic and absolute terms by comparison with traditional methods. The second is an architectural feature that processes pairs of points chosen from two point sets in time proportional to the product of the sizes of those sets, but with input and output volume proportional only to their sum. Together, these features allow Anton to perform pairwise interactions with very high throughput and unusually low latency, enabling MD simulations on time scales inaccessible to other general- and special-purpose parallel systems.

One of the major design verification challenges in the development of Anton, a massively parallel special-purpose machine for molecular dynamics, was to provide evidence that computations spanning more than a quadrillion clock cycles will produce valid scientific results. Our verification methodology addressed this problem by using a hierarchy of RTL, architectural, and numerical simulations. Block- and chip-level RTL models were verified by means of extensive co-simulation with a detailed C++ architectural simulator, ensuring that the RTL models could perform the same molecular dynamics computations as the architectural simulator. The output of the architectural simulator was compared to a parallelized numerical simulator that produces bitwise identical results to Anton, and is fast enough to verify the long-term numerical stability of computations on Anton. These explicit couplings between adjacent levels of the simulation hierarchy created a continuous verification chain from molecular dynamics to individual logic gates.

The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macro-molecules could in principle provide answers to some of the most important currently outstanding questions in the fields of biology, chemistry and medicine. A wide range of biologically interesting phenomena, however, occur over time scales on the order of a millisecond--about three orders of magnitude beyond the duration of the longest current MD simulations.

Providing a single hash function for use across multiple applications is challenging due to the fact that different applications require different sizes of hashed values. An application-independent hash function must be robust in the sense that it must maintain good characteristics independent of the number of output bits which are used. In this paper we show how the BCH construction can be used to construct a single n/spl rarr/m bit linear hash function with the property that that the n/spl rarr/m' bit subhash functions obtained by discarding the upper m - m' output bits all have provably good collision avoidance properties. We apply this technique to the construction of a 256/spl rarr/128 bit hash function. We find that of the 256/spl rarr/m' subhashes, over 78% have optimal minimum collision distances and all but one have a minimum collision distance within 2 of optimal.

We present a simple analytical model for communication over a discarding network using a fault-tolerant messaging protocol. Our technique is an improvement over existing methods in that it accurately models both packet retransmission and the multiple types of packets exchanged between sender and receiver in order to guarantee message delivery and idempotence. The model can be applied to any network and routing strategy; we consider both circuit switching and wormhole routing on three different network topologies. In all cases, the model agrees closely with simulated results.

As parallel machines scale to one million nodes and beyond, it becomes increasingly difficult to build a reliable network that is able to guarantee packet delivery. Eventually large systems will need to employ fault-tolerant messaging protocols that afford correct execution in the presence of a lossy network. In this paper we present a lightweight protocol that preserves message idempotence and is easy to implement in hardware. We identify the requirements for a correct implementation of the protocol. Experiments are performed in simulation to determine implementation parameters that optimize performance. We find that an aggressive implementation on a fat tree network results in a slowdown of less than 2x compared to buffered wormhole routing on a fault-free network.

Out-of-order issue mechanisms increase performance by dynamically rescheduling instructions that cannot be statically reordered by the compiler. Such mechanisms are effective but expensive in terms of both complexity and silicon area. It is therefore desirable to find cost-effective alternatives which can provide similar performance gains. In this paper we present delayed issue, a novel technique which allows instructions to be executed out-of-order without the hardware complexity of dynamic out-of-order issue. Instructions are inserted into per-functional unit delay queues using delays specified by the compiler. Instructions within a queue are issued in order; out of order execution results from different instructions being inserted into the queues at various delays. In addition to improving performance, delayed issue reduces code bloat when loops are pipelined.