{"id":11818,"date":"2026-03-09T03:04:08","date_gmt":"2026-03-09T03:04:08","guid":{"rendered":"https:\/\/mcsoc-forum.org\/site\/?page_id=11818"},"modified":"2026-03-09T03:04:43","modified_gmt":"2026-03-09T03:04:43","slug":"neurocore-t7","status":"publish","type":"page","link":"https:\/\/mcsoc-forum.org\/site\/index.php\/neurocore-t7\/","title":{"rendered":"Simulation, Benchmarking, and Evaluation of Neuromorphic Systems"},"content":{"rendered":"\n<p>The <strong>Track on Simulation, Benchmarking, and Evaluation of Neuromorphic Systems<\/strong> invites high\u2011quality submissions that advance the methodologies, tools, and frameworks used to analyze, validate, and compare neuromorphic hardware and spiking neural network (SNN) platforms. As neuromorphic computing rapidly expands across edge intelligence, robotics, and large\u2011scale cognitive systems, rigorous evaluation is essential to ensure reproducibility, fairness, and meaningful progress. This track brings together researchers from architecture, circuits, computational neuroscience, machine learning, and systems engineering to establish the next generation of simulation and benchmarking practices for neuromorphic technologies.<\/p>\n\n\n\n<p>We welcome original contributions including, but not limited to:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Simulation Frameworks and Tools<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Full\u2011system simulators for neuromorphic processors and SNN accelerators<\/li>\n\n\n\n<li>Mixed\u2011signal, analog, and device\u2011level simulation environments<\/li>\n\n\n\n<li>Multi\u2011scale simulation (device \u2192 circuit \u2192 architecture \u2192 system)<\/li>\n\n\n\n<li>Real\u2011time and hardware\u2011in\u2011the\u2011loop simulation platforms<\/li>\n\n\n\n<li>Co\u2011simulation of neuromorphic hardware with event\u2011based sensors<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Benchmarking Methodologies<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Standardized benchmarks for SNNs, event\u2011driven processing, and neuromorphic workloads<\/li>\n\n\n\n<li>Evaluation suites for robotics, sensorimotor control, and edge intelligence<\/li>\n\n\n\n<li>Benchmarking of learning rules (STDP, R\u2011STDP, Hebbian, supervised SNN training)<\/li>\n\n\n\n<li>Metrics for latency, energy, throughput, accuracy, robustness, and scalability<\/li>\n\n\n\n<li>Comparative studies across digital, analog, mixed\u2011signal, and memristive systems<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. Performance Evaluation and Analysis<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Power, thermal, and reliability characterization of neuromorphic platforms<\/li>\n\n\n\n<li>Variability\u2011aware evaluation for analog and emerging\u2011device systems<\/li>\n\n\n\n<li>Communication and interconnect performance analysis for spike\u2011based traffic<\/li>\n\n\n\n<li>End\u2011to\u2011end evaluation of neuromorphic pipelines (sensing \u2192 processing \u2192 action)<\/li>\n\n\n\n<li>Profiling tools and instrumentation for neuromorphic hardware<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. Algorithms, Mapping, and Co\u2011Design Evaluation<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Evaluation of mapping, partitioning, and scheduling strategies for large SNNs<\/li>\n\n\n\n<li>Co\u2011design methodologies linking algorithms to hardware constraints<\/li>\n\n\n\n<li>Quantization, compression, and sparsity analysis for neuromorphic workloads<\/li>\n\n\n\n<li>Software frameworks enabling reproducible evaluation<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>5. Applications and Case Studies<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Real\u2011world deployments in robotics, autonomous systems, and edge AI<\/li>\n\n\n\n<li>Event\u2011based vision, audition, and tactile processing benchmarks<\/li>\n\n\n\n<li>Biomedical and brain\u2013machine interface evaluation<\/li>\n\n\n\n<li>Comparative studies of neuromorphic vs. conventional AI systems<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Track on Simulation, Benchmarking, and Evaluation of Neuromorphic Systems invites high\u2011quality submissions that advance the methodologies, tools, and frameworks used to analyze, validate, and compare neuromorphic hardware and spiking neural network (SNN) platforms. As neuromorphic computing rapidly expands across edge intelligence, robotics, and large\u2011scale cognitive systems, rigorous evaluation is essential to ensure reproducibility, fairness, &hellip; <\/p>\n<p><a class=\"more-link btn\" href=\"https:\/\/mcsoc-forum.org\/site\/index.php\/neurocore-t7\/\">Continue reading<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-11818","page","type-page","status-publish","hentry","nodate","item-wrap"],"_links":{"self":[{"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/pages\/11818","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/comments?post=11818"}],"version-history":[{"count":1,"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/pages\/11818\/revisions"}],"predecessor-version":[{"id":11819,"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/pages\/11818\/revisions\/11819"}],"wp:attachment":[{"href":"https:\/\/mcsoc-forum.org\/site\/index.php\/wp-json\/wp\/v2\/media?parent=11818"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}