会议信息

ISPASS 2027: International Symposium on Performance Analysis of Systems and Software

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截稿日期:
2026-12-11 还有 32 天
通知日期:
2027-03-08
会议日期:
2027-05-09
会议地点:
New York City, New York, USA
届数:
加入日历: Google 日历 · Outlook / Apple 日历（.ics）
CCF: C   ICORE: B   QUALIS: B1   浏览: 39760   关注: 49   参加: 7
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ISPASS
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搜索与榜单列表完全无需凭证；本页的完整详情需要一把免费 API 密钥。详见开发者接入页。

会伴指数 (CP-I)

55.4 / 100
全站第 870 名 / 共 5,771 个会议 · 前 16%

软件工程 第 86 / 249

学术认可 (35%)
78
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
19
社区关注 (10%)
62
资料公开度 (15%)
55

用到的输入: 收录等级：CCF C, ICORE B, QUALIS B1 · 有据可查的届次：1 · 在会伴关注它的研究者：49 人 · 过去 24 个月打开过本页的研究者：23 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 80% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-11-09

这些机构的科研人员在跟踪这个会议

East China Normal University 3
Peking University 3
University of Chinese Academy of Sciences 3

依据科研人员在个人资料中自行填写的机构，我们不做核验。

征稿

ISPASS 2027 (International Symposium on Performance Analysis of Systems and Software) is a CCF C / ICORE B / QUALIS B1 conference held in New York City, New York, USA on 2027-05-09. The paper submission deadline is 2026-12-11. Acceptance notifications are sent on 2027-03-08.

The IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) provides a forum for sharing advanced academic and industrial research focused on performance analysis in the design of computer systems and software. Authors are invited to submit previously unpublished work for possible presentation at the conference. ISPASS 2027 will be held in New York City on May 9–11, 2027. Topics of interest Papers are solicited in fields that include the following. Methodology Performance and efficiency (power, area, and so on) evaluation methodologies Analytical modelling Statistical approaches Tracing and profiling tools Simulation techniques Hardware-accelerated simulation, for example on FPGAs Hardware performance counter architectures Power, temperature, variability and reliability models for computer systems Microbenchmark-based hardware analysis techniques Foundations of performance and efficiency analysis Metrics Bottleneck identification and analysis Visualization Analysis of commercial and experimental hardware Multi-threaded, multicore and many-core architectures Accelerators and graphics processing units Memory systems, including storage-class memory Embedded and mobile systems Enterprise systems and data centers HPC and supercomputers Computer networks Quantum computing Emerging technologies Analysis of emerging workloads and software Software written in managed languages Virtualization and consolidation workloads Datacenter and internet-sector workloads Embedded, multimedia, games, telepresence Machine learning training and inference workloads Application and system code tuning and optimization Confirmations or refutations of important prior results
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