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| Content Provider | ACM Digital Library |
|---|---|
| Author | Bugnion, Edouard Grot, Boris Daglis, Alexandros Novaković, Stanko Falsafi, Babak |
| Abstract | Datacenter operators rely on low-cost, high-density technologies to maximize throughput for data-intensive services with tight tail latencies. In-memory rack-scale computing is emerging as a promising paradigm in scale-out datacenters capitalizing on commodity SoCs, low-latency and high-bandwidth communication fabrics and a remote memory access model to enable aggregation of a rack's memory for critical data-intensive applications such as graph processing or key-value stores. Low latency and high bandwidth not only dictate eliminating communication bottlenecks in the software protocols and off-chip fabrics but also a careful on-chip integration of network interfaces. The latter is a key challenge especially in architectures with RDMA-inspired one-sided operations that aim to achieve low latency and high bandwidth through on-chip Network Interface (NI) support. This paper proposes and evaluates network interface architectures for tiled manycore SoCs for in-memory rack-scale computing. Our results indicate that a careful splitting of NI functionality per chip tile and at the chip's edge along a NOC dimension enables a rack-scale architecture to optimize for both latency and bandwidth. Our best manycore NI architecture achieves latencies within 3% of an idealized hardware NUMA and efficiently uses the full bisection bandwidth of the NOC, without changing the on-chip coherence protocol or the core's microarchitecture. |
| Starting Page | 567 |
| Ending Page | 579 |
| Page Count | 13 |
| File Format | |
| ISSN | 01635964 |
| DOI | 10.1145/2872887.2750415 |
| Journal | ACM SIGARCH Computer Architecture News (CARN) |
| Volume Number | 43 |
| Issue Number | 3 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1981-04-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
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