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FPGA 2027: International Symposium on Field-Programmable Gate Arrays

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Submission Date:
2026-10-01 Due in 13 days
Notification Date:
2026-11-24
Conference Date:
2027-03-14
Location:
Seaside, California, USA
Years:
CCF: B   ICORE: A   QUALIS: A2   Viewed: 68445   Tracked: 72   Attend: 7

Conference Partner Index (CP-I)

78.3 / 100
Ranked #218 of 5,682 conferences · Top 4%

#44 of 341 in Systems & Architecture

Academic recognition (35%)
92
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
96
Community attention (10%)
63
Public record completeness (15%)
70

Inputs used: Listed as CCF B, ICORE A, QUALIS A2 · Editions on record: 35 · Researchers following it here: 72 · Researchers who opened this page in the past 24 months: 16

Missing from the public record: Historical acceptance rates (+4.5)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-17

Call For Papers

FPGA 2027 (International Symposium on Field-Programmable Gate Arrays) is a CCF B / ICORE A / QUALIS A2 conference held in Seaside, California, USA on 2027-03-14. The paper submission deadline is 2026-10-01. Acceptance notifications are sent on 2026-11-24.

The ACM/SIGDA International Symposium on Field-Programmable Gate Arrays is the premier conference for the presentation of advances in FPGA technology. In March 2027, the 35th edition of ISFPGA will be held in California, USA. Accepted papers will be published in the conference proceedings and available in the ACM Digital Library. Submission Topics FPGA’s scope includes spatial architectures more broadly, including coarse-grained reconfigurable arrays (CGRAs), neural processing units (NPUs), AI Engines, and other dataflow/spatial computing fabrics, alongside our core FPGA focus. We solicit research papers in the following topic areas: FPGA and Spatial Architecture Design: Architectures for programmable logic fabrics, CGRAs, NPUs, AI Engines, and other spatial compute fabrics, including routing/interconnect, reconfigurable logic or processing elements, embedded blocks (memory, DSP, processors), and I/O interfaces. Novel commercial and open-source architectures and architectural features. FPGA Circuit Design: Circuits and layout techniques for the design of FPGAs and spatial fabrics. Impacts of future process and design technologies on FPGAs as well as novel memory or nanoscale devices. Methods for analyzing and improving static and dynamic power consumption, power and clock distribution, yield, manufacturability, security, reliability, and testability. CAD for FPGAs and Spatial Architectures: Algorithms for synthesis, technology mapping, logic and timing optimization, clustering, placement, and routing on FPGAs as well as scheduling/mapping for spatial and dataflow architectures. Novel design software for system-level partitioning, debug, and verification. Algorithms for modeling, analysis, and optimization of timing and power. High-Level Abstractions and Tools: General-purpose and domain-specific languages, tools, and techniques to facilitate the design, debugging, or verification of applications targeting FPGAs and spatial architectures. Novel hardware/software co-design and high-level synthesis methodologies enabling mapping of specialized applications onto FPGAs and spatial architectures. FPGA-based and FPGA-like Computing Engines: Systems and software for compiled accelerators on spatial computing engines/NPUs or programmable overlay architectures implemented using FPGAs. Applications and Design Studies: Implementation of novel designs on FPGAs or spatial architectures establishing state-of-the-art in high-performance, low-power, security, or high-reliability. Designs leveraging unique capabilities of these architectures or demonstrating significant improvements over alternative programmable technologies (e.g., CPU, GPU). Design studies and architecture explorations enabling CAD and architecture improvements. AI/ML for and on FPGAs and Spatial Architectures: FPGA-based accelerators for AI/ML algorithms, such as Large Language Models and World Models and implementations on spatial architectures. Novel uses of AI models to aid in the design and programming of FPGAs.
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