Analytics with smart arrays: adaptive and efficient language-independent data Psaroudakis et al., EuroSys'18 (If you don’t have ACM Digital Library access, the paper can be accessed either by following the link above directly from The Morning Paper blog site). We’re going lower-level today, with a look at some work on adaptive data structures by Oracle. … Continue reading Analytics with smart arrays: adaptive and efficient language-independent data
Tag: Hardware
Advances in hardware (typically as it relates to the software that runs on top).
Azure accelerated networking: SmartNICs in the public cloud
Azure accelerated networking: SmartNICs in the public cloud Firestone et al., NSDI'18 We’re still on the ‘beyond CPUs’ theme today, with a great paper from Microsoft detailing their use of FPGAs to accelerate networking in Azure. Microsoft have been doing this since 2015, and hence this paper also serves as a wonderful experience report documenting … Continue reading Azure accelerated networking: SmartNICs in the public cloud
NetChain: Scale-free sub-RTT coordination
NetChain: Scale-free sub-RTT coordination Jin et al., NSDI'18 NetChain won a best paper award at NSDI 2018 earlier this month. By thinking outside of the box (in this case, the box is the chassis containing the server), Jin et al. have demonstrated how to build a coordination service (think Apache ZooKeeper) with incredibly low latency … Continue reading NetChain: Scale-free sub-RTT coordination
SmoothOperator: reducing power fragmentation and improving power utilization in large-scale datacenters
SmoothOperator: reducing power fragmentation and improving power utilization in large-scale datacenters Hsu et al., ASPLOS'18 What do you do when your theory of constraints analysis reveals that power has become your major limiting factor? That is, you can’t add more servers to your existing datacenter(s) without blowing your power budget, and you don’t want to … Continue reading SmoothOperator: reducing power fragmentation and improving power utilization in large-scale datacenters
Espresso: brewing Java for more non-volatility with non-volatile memory
Espresso: brewing Java for more non-volatility with non-volatile memory Wu et al., ASPLOS'18 What happens when you introduce non-volatile memory (NVM) to the world of Java? In theory, with a heap backed by NVM, we should get persistence for free? It’s not quite that straightforward of course, but Espresso gets you pretty close. There are … Continue reading Espresso: brewing Java for more non-volatility with non-volatile memory
The architectural implications of autonomous driving: constraints and acceleration
The architectural implications of autonomous driving: constraints and acceleration Lin et al., ASPLOS'18 Today’s paper is another example of complementing CPUs with GPUs, FPGAs, and ASICs in order to build a system with the desired performance. In this instance, the challenge is to build an autonomous self-driving car! Architecting autonomous driving systems is particularly challenging … Continue reading The architectural implications of autonomous driving: constraints and acceleration
Darwin: a genomics co-processor provides up to 15,000x acceleration on long read assembly
Darwin: a genomics co-processor provides up to 15,000x acceleration on long read assembly Turakhia et al., ASPLOS'18 With the slow demise of Moore’s law, hardware accelerators are needed to meet the rapidly growing computational requirements of X. For this paper, X = genomics, and genomic data is certainly growing fast: doubling every 7 months and … Continue reading Darwin: a genomics co-processor provides up to 15,000x acceleration on long read assembly
Google workloads for consumer devices: mitigating data movement bottlenecks
Google workloads for consumer devices: mitigating data movement bottlenecks Boroumand et al., ASPLOS'18 What if your mobile device could be twice as fast on common tasks, greatly improving the user experience, while at the same time significantly extending your battery life? This is the feat that the authors of today’s paper pull-off, using a technique … Continue reading Google workloads for consumer devices: mitigating data movement bottlenecks
KV-Direct: High-performance in-memory key-value store with programmable NIC
KV-Direct: High-performance in-memory key-value store with programmable NIC Li et al., SOSP’17 We’ve seen some pretty impressive in-memory datastores in past editions of The Morning Paper, including FaRM, RAMCloud, and DrTM. But nothing that compares with KV-Direct: With 10 programmable NIC cards in a commodity server, we achieve 1.22 billion KV operations per second, which … Continue reading KV-Direct: High-performance in-memory key-value store with programmable NIC
Towards deploying decommissioned mobile devices as cheap energy-efficient compute nodes
Towards deploying decommissioned mobile devices as cheap energy-efficient compute nodes Shahrad & Wentzlaff, HotCloud'17 I have one simple rule when it comes to selecting papers for The Morning Paper: I only cover papers that I like and find interesting. There are some papers though, that manage to generate in me a genuine feeling of excitement, … Continue reading Towards deploying decommissioned mobile devices as cheap energy-efficient compute nodes
the morning paper 