In this paper, we propose a highly efficient computing method for game character control with phase-functioned neural networks (PFNN). The primary challenge to accelerate PFNN on mobile platforms is that PFNN dynamically produces weight matrices with an ...

Ever-growing CNN size incurs a significant amount of redundancy in model parameters, which in turn, puts considerable burden on hardware. Unstructured pruning is widely used to reduce model sparsity. While, the irregularity introduced by unstructured ...

Full batch training of Graph Convolutional Network (GCN) models is not feasible on a single GPU for large graphs containing tens of millions of vertices or more. Recent work has shown that, for the graphs used in the machine learning community, ...

Most flash-based solid-state drives (SSDs) employ an on-board Dynamic Random Access Memory (DRAM) to cache hot data at the SSD page granularity. This can significantly reduce the number of flush operations to the underlying arrays of SSDs given that ...

The challenges of low latency, high throughput datacenter networks create new traffic management problems that require new congestion control mechanisms. Generally, the proposals to solve this problem have focused either on refining existing window-...

Federated learning (FL) has emerged as a new paradigm that enables distributed mobile devices to learn a global model collaboratively. Since mobile devices (a.k.a, clients) exhibit diversity in model training quality, client selection (CS) becomes ...

Atomic broadcast protocols ensure that messages are delivered to a group of machines in some total order, even when some of these machines can fail. These protocols are key to making distributed services fault-tolerant, as their total order guarantee ...

Modern clustered storage systems increasingly adopt erasure coding to realize reliable data storage at low storage redundancy. Locally Repairable Codes (LRC) are a family of practical erasure codes with high repair efficiency. Among various LRC ...

Parity-based RAID suffering from partial-stripe write-penalty has to introduce write buffer to fast absorb and merge incoming writes, and then flush them to RAID array in batch. However, we experimentally observe that the popular buffering mechanism as ...

Large-scale distributed storage systems have introduced erasure code to guarantee high data reliability, yet inevitably at the expense of high repair costs. In practice, storage nodes are usually divided into different racks, and data blocks in storage ...

Sparse matrix-sparse vector multiplication (SpMSpV) is an important primitive for graph algorithms and machine learning applications. The sparsity of the input and output vectors makes its floating point efficiency in general lower than sparse matrix-...

Inter-process communications form a performance bottleneck for large-scale brain simulations. The sparse and imbalanced communication patterns of human brain make it particularly challenging to design a communication system for supporting large-scale ...