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Understanding operational 5G: a first measurement study on its coverage, performance and energy consumption

The Morning Paper

Understanding operational 5G: a first measurement study on its coverage, performance and energy consumption , Xu et al., What is the end-to-end throughput and latency, and where are the bottlenecks? energy consumption). Future 5G Standalone Architecture (SA) deployments with a native 5G control plane will not have this problem.

Energy 130
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What is a Distributed Storage System

Scalegrid

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130
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Boosted race trees for low energy classification

The Morning Paper

Boosted race trees for low energy classification Tzimpragos et al., We don’t talk about energy as often as we probably should on this blog, but it’s certainly true that our data centres and various IT systems consume an awful lot of it. One efficient way of doing that in analog hardware is the use of current-starved inverters.

Energy 52
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Current status, needs, and challenges in Heterogeneous and Composable Memory from the HCM workshop (HPCA’23)

ACM Sigarch

Introduction Memory systems are evolving into heterogeneous and composable architectures. There are three common mechanisms to access remote memory: modifying applications, modifying virtual memory, and hardware-level cache coherence support. Figure 2: Latency characteristics of memory technologies (source: Maruf et al.,

Latency 52
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Achieving 100Gbps intrusion prevention on a single server

The Morning Paper

This makes the whole system latency sensitive. So we need low latency, but we also need very high throughput: A recurring theme in IDS/IPS literature is the gap between the workloads they need to handle and the capabilities of existing hardware/software implementations. The target FPGA for Pigasus has 16MB of BRAM.

Servers 128
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A case for managed and model-less inference serving

The Morning Paper

As we saw with the SOAP paper last time out, even with a fixed model variant and hardware there are a lot of different ways to map a training workload over the available hardware. The following figure highlights how just one of these variables, batch size, impacts throughput and latency on ResNet50.

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Intel discloses “vector+SIMD” instructions for future processors

John McCalpin

The art and science of microprocessor architecture is a never-ending struggling to balance complexity, verifiability, usability, expressiveness, compactness, ease of encoding/decoding, energy consumption, backwards compatibility, forwards compatibility, and other factors. This includes Haswell and newer cores.

Cache 40