feat: mindc 0.2.3 — remove XRM/ASIC, add use keyword parser

Breaking: removed XRM-SSD ASIC target dialect (not part of MIND core)
  - Deleted src/mlir/asic_target.rs (355 lines)
  - Deleted examples/xrm_inference.mind
  - Removed BackendTarget::Asic variant
  - Removed "asic" | "xrm" CLI parser branch

Parser: added `use` keyword as alias for `import`
  - parse_use() handles `use module.path` syntax
  - Enables MIND modules to use standard `use` declarations
  - Required for multi-module projects (fim-onsager-experiment)

Tests: 5 passed, 0 failed. Criterion: zero regression.

Author: star-ga

ANATOMY.md

@@ -5,8 +5,8 @@
 > Re-generate with: `anatomy .`
 
 **Project:** `mind`
-**Files:** 332 | **Est. tokens:** ~432,162
-**Generated:** 2026-04-02 04:39 UTC
+**Files:** 330 | **Est. tokens:** ~427,489
+**Generated:** 2026-04-11 04:00 UTC
 
 ## Token Budget Guide
 
@@ -39,7 +39,7 @@
 | `docs/design/` | 2 | ~136 |
 | `docs/rfcs/` | 4 | ~1,081 |
 | `docs/specs/` | 2 | ~976 |
-| `examples/` | 15 | ~33,738 |
+| `examples/` | 14 | ~31,974 |
 | `examples/c/` | 2 | ~400 |
 | `examples/compliance/` | 3 | ~5,294 |
 | `examples/zoo/` | 6 | ~12,885 |
@@ -52,7 +52,7 @@
 | `src/` | 7 | ~14,732 |
 | `src/ast/` | 1 | ~1,784 |
 | `src/autodiff/` | 3 | ~4,159 |
-| `src/bin/` | 2 | ~10,471 |
+| `src/bin/` | 2 | ~10,458 |
 | `src/diagnostics/` | 1 | ~2,230 |
 | `src/eval/` | 12 | ~51,907 |
 | `src/eval/stdlib/` | 2 | ~8,515 |
@@ -61,13 +61,13 @@
 | `src/ir/` | 3 | ~5,639 |
 | `src/ir/compact/` | 3 | ~13,890 |
 | `src/ir/compact/v2/` | 6 | ~15,796 |
-| `src/mlir/` | 3 | ~7,361 |
+| `src/mlir/` | 2 | ~4,330 |
 | `src/ops/` | 2 | ~2,047 |
-| `src/opt/` | 4 | ~6,479 |
+| `src/opt/` | 4 | ~6,469 |
 | `src/package/` | 2 | ~1,668 |
-| `src/parser/` | 1 | ~13,957 |
+| `src/parser/` | 1 | ~14,135 |
 | `src/project/` | 1 | ~9,268 |
-| `src/runtime/` | 3 | ~1,001 |
+| `src/runtime/` | 3 | ~968 |
 | `src/shapes/` | 2 | ~6,051 |
 | `src/stdlib/` | 2 | ~560 |
 | `src/type_checker/` | 1 | ~14,918 |
@@ -282,7 +282,6 @@
 - `remizov_solver.mind` (~3699 tok, huge) — Copyright 2025-2026 STARGA Inc.
 - `remizov_verify.mind` (~3618 tok, huge) — Copyright 2025-2026 STARGA Inc.
 - `tiny_edge_model.mind` (~1900 tok, huge) — Tiny Edge Model Example
-- `xrm_inference.mind` (~1764 tok, huge) — XRM Inference Test — real-number verification of cognitive kernels
 ### `examples/zoo/`
 
 - `conv_classifier.mind` (~2518 tok, huge) — CNN Classifier — MIND Model Zoo
@@ -334,7 +333,7 @@
 ### `src/bin/`
 
 - `mind-ai.rs` (~6045 tok, huge) — Copyright 2025 STARGA Inc.
-- `mindc.rs` (~4426 tok, huge) — Copyright 2025 STARGA Inc.
+- `mindc.rs` (~4413 tok, huge) — Copyright 2025 STARGA Inc.
 ### `src/`
 
 - `conformance.rs` (~1871 tok, huge)
@@ -396,9 +395,8 @@
 - `main.rs` (~6501 tok, huge) — Copyright 2025 STARGA Inc.
 ### `src/mlir/`
 
-- `asic_target.rs` (~3010 tok, huge) — Copyright 2025-2026 STARGA Inc.
 - `lowering.rs` (~4060 tok, huge) — Copyright 2025 STARGA Inc.
-- `mod.rs` (~291 tok, medium) — Copyright 2025 STARGA Inc.
+- `mod.rs` (~270 tok, medium) — Copyright 2025 STARGA Inc.
 ### `src/ops/`
 
 - `core_v1.rs` (~1823 tok, huge) — Copyright 2025 STARGA Inc.
@@ -407,15 +405,15 @@
 
 - `fold.rs` (~824 tok, large) — Copyright 2025 STARGA Inc.
 - `ir_canonical.rs` (~1415 tok, large) — Copyright 2025 STARGA Inc.
-- `memory_layout.rs` (~4060 tok, huge) — Copyright 2025-2026 STARGA Inc.
+- `memory_layout.rs` (~4050 tok, huge) — Copyright 2025-2026 STARGA Inc.
 - `mod.rs` (~180 tok, small) — Copyright 2025 STARGA Inc.
 ### `src/package/`
 
 - `manifest.rs` (~310 tok, medium) — Copyright 2025 STARGA Inc.
 - `mod.rs` (~1358 tok, large) — Copyright 2025 STARGA Inc.
 ### `src/parser/`
 
-- `mod.rs` (~13957 tok, huge) — Copyright 2025 STARGA Inc.
+- `mod.rs` (~14135 tok, huge) — Copyright 2025 STARGA Inc.
 ### `src/`
 
 - `pipeline.rs` (~1853 tok, huge) — Copyright 2025 STARGA Inc.
@@ -434,7 +432,7 @@
 ### `src/runtime/`
 
 - `mod.rs` (~92 tok, small) — Runtime abstractions for execution backends.
-- `types.rs` (~621 tok, large) — Shared runtime surface types for execution backends.
+- `types.rs` (~588 tok, large) — Shared runtime surface types for execution backends.
 ### `src/shapes/`
 
 - `engine.rs` (~1882 tok, huge) — A rank-N tensor shape represented as a list of extents.

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "mind"
-version = "0.2.1"
+version = "0.2.3"
 edition = "2021"
 rust-version = "1.82"
 authors = ["STARGA Inc."]

benchmarks/inference/inference_results.json

@@ -1,61 +1,61 @@
 {
   "system_info": {
-    "platform": "Linux-6.17.0-14-generic-x86_64-with-glibc2.39",
+    "platform": "Linux-6.17.0-19-generic-x86_64-with-glibc2.39",
     "python_version": "3.12.3",
-    "pytorch_version": "2.10.0+cu128",
+    "pytorch_version": "2.11.0+cu126",
     "cpu": "x86_64",
     "cuda_available": true,
-    "cuda_version": "12.8",
+    "cuda_version": "12.6",
     "gpu": "NVIDIA GeForce RTX 3080"
   },
   "benchmarks": {
     "large_matmul_4096": {
       "pytorch": {
-        "latency_mean_us": 135.3842081152834,
-        "latency_stdev_us": 42.942990440874205,
-        "latency_min_us": 120.7859895657748,
-        "latency_max_us": 364.03900594450533,
-        "throughput_samples_per_sec": 7386.385856380475,
+        "latency_mean_us": 127.97151342965662,
+        "latency_stdev_us": 7.563694781582514,
+        "latency_min_us": 120.82199100404978,
+        "latency_max_us": 154.23703007400036,
+        "throughput_samples_per_sec": 7814.239069304123,
         "batch_size": 1
       },
       "mind": {
         "latency_mean_us": 80000.0,
         "throughput_samples_per_sec": 12.5
       },
-      "latency_speedup": 0.0016923026014410425,
-      "throughput_advantage": 0.0016923026014410425
+      "latency_speedup": 0.0015996439178707078,
+      "throughput_advantage": 0.0015996439178707076
     },
     "mlp_batch32": {
       "pytorch": {
-        "latency_mean_us": 182.9913823166862,
-        "latency_stdev_us": 42.8112071096602,
-        "latency_min_us": 161.73897893168032,
-        "latency_max_us": 362.97200131230056,
-        "throughput_samples_per_sec": 174871.62288670277,
+        "latency_mean_us": 181.99977406766266,
+        "latency_stdev_us": 32.01634240033862,
+        "latency_min_us": 168.96100714802742,
+        "latency_max_us": 315.5280137434602,
+        "throughput_samples_per_sec": 175824.39409019955,
         "batch_size": 32
       },
       "mind": {
         "latency_mean_us": 1200.0,
         "throughput_samples_per_sec": 26666.666666666668
       },
-      "latency_speedup": 0.1524928185972385,
-      "throughput_advantage": 0.1524928185972385
+      "latency_speedup": 0.1516664783897189,
+      "throughput_advantage": 0.1516664783897189
     },
     "conv2d_inference": {
       "pytorch": {
-        "latency_mean_us": 333.60577013809234,
-        "latency_stdev_us": 54.44390556596796,
-        "latency_min_us": 291.6759985964745,
-        "latency_max_us": 508.2639981992543,
-        "throughput_samples_per_sec": 23980.40056887652,
+        "latency_mean_us": 310.3324136463925,
+        "latency_stdev_us": 48.69665704083,
+        "latency_min_us": 288.3190172724426,
+        "latency_max_us": 515.4100363142788,
+        "throughput_samples_per_sec": 25778.808942322023,
         "batch_size": 8
       },
       "mind": {
         "latency_mean_us": 5000.0,
         "throughput_samples_per_sec": 1600.0
       },
-      "latency_speedup": 0.06672115402761847,
-      "throughput_advantage": 0.06672115402761847
+      "latency_speedup": 0.062066482729278505,
+      "throughput_advantage": 0.0620664827292785
     }
   }
 }

examples/xrm_inference.mind

@@ -502,7 +502,6 @@ fn parse_target(raw: &str) -> Result<BackendTarget, String> {
     match raw.to_ascii_lowercase().as_str() {
         "cpu" => Ok(BackendTarget::Cpu),
         "gpu" | "cuda" | "rocm" | "metal" | "webgpu" => Ok(BackendTarget::Gpu),
-        "asic" | "xrm" => Ok(BackendTarget::Asic),
         "tpu" => Ok(BackendTarget::Tpu),
         "npu" | "ane" | "hexagon" => Ok(BackendTarget::Npu),
         "lpu" | "groq" => Ok(BackendTarget::Lpu),