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

Securing wireless neurostimulators

Securing wireless neurostimulators Marin et al., CODASPY'18 There’s a lot of thought-provoking material in this paper. The subject is the security of a class of Implantable Medical Devices (IMD) called neurostimulators. These are devices implanted under the skin near the clavicle, and connected directly to the patient’s brain through several leads. They can help to … Continue reading Securing wireless neurostimulators

PrivacyGuide: towards an implementation of the EU GDPR on Internet privacy policy evaluation

PrivacyGuide: Towards an implementation of the EU GDPR on Internet privacy policy evaluation Tesfay et al., IWSPA'18 (Note: the above link takes you to the ACM Digital Library, where the paper should be accessible when accessed from the blog site. If you’re reading this via the email subscription and don’t have ACM DL access, please … Continue reading PrivacyGuide: towards an implementation of the EU GDPR on Internet privacy policy evaluation