The ASPLOS'18 program is the result of a thorough evaluation process, which we started by forming the program committee (PC) with 50 members and the external review committee (ERC) with 73 members. Moreover, we split up the PC into two independent sub-PCs while keeping the ERC as a single unit. We carefully assigned the PC members to the two groups, ensuring that (1) each sub-PC would cover all ASPLOS topics and (2) the experts on each topic would be evenly split across the sub-PCs. In response to the call for papers, we received 319 submissions, just one shy of last year's record. (This number includes 18 submissions that were either withdrawn by their authors or desk-rejected for clear violations of the formatting rules.) After receiving reviewing bids from most committee members, we also split the submissions evenly across the two sub-PCs, so that each submission would receive reviews from only one sub-PC. We manually moved submissions across sub-PCs to maximize reviewer expertise, according to the PC members' bids. The review process proceeded in two rounds, followed by an extensive online discussion period. During the first round, all submissions received 3-4 reviews. Based on these reviews, we selected 158 submissions to go through the second round of reviews, which produced 2-4 additional reviews for these submissions. During the review process, we also requested reviews from 52 external experts on a case-by-case basis. Throughout the process, our main goal in assigning reviewers to submissions was to maximize reviewer expertise. Overall, the committees and external experts produced 1,227 reviews. After the online discussion period involving all reviewers, we selected 100 submissions for discussion (15 papers online-tagged tentative-accepts and 85 papers online-tagged discuss-at-meeting) during the PC meeting on November 10, 2017 at Georgia Tech. 47 of the 50 PC members were physically present at the meeting and 2 others participated remotely. The whole committee met together in the morning, and split up into the two independent sub- PCs in the afternoon. We did not set a limit for the number of accepted submissions. During the meeting, we accepted 47 submissions and conditionally accepted (subject to shepherding) 9 others. After carefully addressing the reviewers' comments, all shepherded submissions were ultimately accepted. The acceptance rate of the two sub-PCs was exactly the same: 28/151 and 28/150. To complete the program, we invited two outstanding keynote speakers: Hillery Hunter (IBM Research) and Fred Chong (University of Chicago). We are pleased that the 56 accepted submissions and 2 keynote talks represent an exciting spectrum of traditional and emerging ASPLOS topics.
SOFRITAS: Serializable Ordering-Free Regions for Increasing Thread Atomicity Scalably
Correctly synchronizing multithreaded programs is challenging and errors can lead to program failures such as atomicity violations. Existing strong memory consistency models rule out some possible failures, but are limited by depending on programmer-...
DAMN: Overhead-Free IOMMU Protection for Networking
DMA operations can access memory buffers only if they are "mapped" in the IOMMU, so operating systems protect themselves against malicious/errant network DMAs by mapping and unmapping each packet immediately before/after it is DMAed. This approach was ...
Google Workloads for Consumer Devices: Mitigating Data Movement Bottlenecks
- Amirali Boroumand,
- Saugata Ghose,
- Youngsok Kim,
- Rachata Ausavarungnirun,
- Eric Shiu,
- Rahul Thakur,
- Daehyun Kim,
- Aki Kuusela,
- Allan Knies,
- Parthasarathy Ranganathan,
- Onur Mutlu
We are experiencing an explosive growth in the number of consumer devices, including smartphones, tablets, web-based computers such as Chromebooks, and wearable devices. For this class of devices, energy efficiency is a first-class concern due to the ...
Watching for Software Inefficiencies with Witch
Inefficiencies abound in complex, layered software. A variety of inefficiencies show up as wasteful memory operations. Many existing tools instrument every load and store instruction to monitor memory, which significantly slows execution and consumes ...
Cited By
- Chen Y, Pei L and Carlson T AfterImage: Leaking Control Flow Data and Tracking Load Operations via the Hardware Prefetcher Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2, (16-32)
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Sarker M, Saad M, Riaz A, Lipu M and Olazagoitia J (2022). Micro Energy Storage Systems in Energy Harvesting Applications: Analytical Evaluation towards Future Research Improvement, Micromachines, 10.3390/mi13040512, 13:4, (512)
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
ASPLOS '19 | 351 | 74 | 21% |
ASPLOS '18 | 319 | 56 | 18% |
ASPLOS '17 | 320 | 53 | 17% |
ASPLOS '16 | 232 | 53 | 23% |
ASPLOS '15 | 287 | 48 | 17% |
ASPLOS '14 | 217 | 49 | 23% |
ASPLOS XV | 181 | 32 | 18% |
ASPLOS XIII | 127 | 31 | 24% |
ASPLOS XII | 158 | 38 | 24% |
ASPLOS X | 175 | 24 | 14% |
ASPLOS IX | 114 | 24 | 21% |
ASPLOS VIII | 123 | 28 | 23% |
ASPLOS VII | 109 | 25 | 23% |
Overall | 2,713 | 535 | 20% |