Exploiting at best every bit of memory on chip is a must for finding the best trade-off between cost and performance when designing Many-Core MPSoCs. In this paper, we propose a new memory hierarchy organization that maximizes the usage of the available memory at each cache level while avoiding data redundancy. We also aim to reduce data access time by avoiding data migration. Our scheme is based on Non-Uniform Cache Architectures (NUCA), and makes use of a novel NoC multicast messaging support. It requires to logically partition the network into imagined layers in which each layer is bound to one of the cache levels. We assess the efficiency of our proposal by evaluating performance metrics, using the Gem5 simulator and the Splash2 benchmark suite. Our results show an improvement of 24% in L2 miss rate over baseline S_NUCA organization and more than 25% in average network latency. We report a maximum improvement of 40% in execution time. Also, we show that our approach outperforms R_NUCA.

This paper addresses elevator assignment in vertically-partially-connected 3-D-networks-on-chip (NoCs). Elevators are vertical links between dies. Because of yield issues, Through-Silicon-Via (TSV) cost, and heterogeneity in dimension, topology, and technology of different dies, vertically-partially-connected topologies seem unavoidable in the emerging 3-D-NoCs as opposed to fully-connected topologies. In such partially-connected topologies, as there are fewer elevators than routers, the assignment of elevators to routers becomes a new 3-D-specific optimization problem. An improper assignment can lead to dramatic network performance degradation. This paper proposes an elevator assignment method for best-effort wormhole 3-D-NoCs to improve the average network performance. Experimental results show an improvement of about 90% even compared to a greedy (intrinsically good) initial assignment.

In this paper, we propose a distributed routing algorithm for vertically partially connected regular 2D topologies of different shapes and sizes (e.g., 2D mesh, torus, ring). The topologies that are the target of this algorithm are of practical interest in the 3D integration of heterogeneous dies using Through-Silicon-Vias (TSVs). Indeed, TSV-based 3D integration allows to envision the stacking of dies with different functions and technologies, using as an interconnect backbone a 3D-NoC. Intrinsically, 3D topologies have better performances, but yield and active area (and thus the cost) are function of the number of TSVs; therefore, the designs tend to use only a subset of available TSVs between two dies. The definition of blockage free and low implementation cost distributed deterministic routing on this kind of topology is thus of theoretical and practical interests. We formally prove that independently of the shape and dimensions of the planar topologies and of the number and placement of the TSVs, the proposed routing algorithm using two virtual channels in the plane is deadlock and livelock free. We also experimentally show that the performance of this algorithm is still acceptable when the number of vertical connections decreases.

This paper addresses link-buffer capacity allocation in the design process of best-effort 3DNoCs holding hotspot memory ports. We show that in 3DSoCs with integrated wide I/O DRAMs, the congestion spreading is different from SoCs with external DRAMs: the bottlenecks are not anymore the external memory ports but the network links that become saturated and retropropagate the congestion. The distribution of bottleneck links is directly affected by the traffic directed to the hot memory ports. Using an analytical performance evaluation method, we determine network link buffer capacities according to the given workload composed of regular and hotspot traffics.