June 2026 monthly summary focusing on code quality and maintainability improvements within sarchlab/akita. Delivered a single critical bug fix: rename VTimeInSec to VTimeInPicoSec to reflect the actual time unit used across codebase and docs. This change touched 31 Go call sites and 5 documentation references, eliminating inconsistency and reducing potential runtime and onboarding confusion.

May 2026 performance summary for sarchlab/akita: Delivered end-to-end improvements across data reliability, test observability, and frontend stability. Core work included refactoring simulation metadata recording into the simulation package with a new metaRecorder to capture execution start/end times, commands, and working directories; adding tracing support for memory acceptance tests to visualize memory access patterns; and a comprehensive frontend rewrite in React for Daisen2 with improved widget data loading, removal of legacy components and CI, and improved accessibility by repositioning the bot button. These efforts improved data integrity, debugging efficiency, user experience, and reduced maintenance overhead.

March 2026 performance summary focused on expanding CDNA3 benchmark coverage, stabilizing critical paths, and strengthening CI and tooling to deliver measurable business value across MGPSim and Akita. Key work included expanding CDNA3 support for BFS/NW, FFT, SPMV, and N-body benchmarks, plus substantial fixes to CDNA3 struct layouts, FLAT offset decoding, and HSACO integration. Stencil2D CDNA3 page fault and kernel descriptor metadata were resolved, with acceptance tests added to validate end-to-end correctness. The N-body CDNA3 fix used a safer GCN3 kernel path to eliminate data races and simplify usage. In Ares, we introduced -bytes flag support, CLI flag for FFT benchmarking, FFT sub-MB sizes, and timing model sync for M2.1 benchmarks, along with a DRAM modeling update via simplebankedmemory and CI/linter improvements, increasing reliability and throughput of benchmarks. MI300A calibration achieved 16.4% WMAPE accuracy across 206 matched points, signaling improved timing and memory behavior models. Cross-repo, Akita upgraded the SQLite driver to glebarez/go-sqlite (pure Go) for better compatibility and performance. Overall impact: broader hardware coverage, higher correctness, faster feedback loops, and improved stability that directly supports faster decision-making and more reliable performance projections.