record_uuid stringlengths 36 36 | target_hardware_platform stringclasses 2
values | problem_statement stringlengths 562 604 | naive_cpu_code_reference stringclasses 4
values | failed_triton_attempt stringlengths 411 480 | compiler_exception_class stringclasses 3
values | execution_error_log stringclasses 3
values | expert_root_cause_analysis stringclasses 3
values | fixed_triton_code stringlengths 539 591 | pipeline_metadata dict |
|---|---|---|---|---|---|---|---|---|---|
26af6908-60bf-4d71-b64c-1a36677c0169 | NVIDIA H100 SXM5 (Hopper) | Task: Implement a high-performance raw Triton GPU kernel variant for a 'Fused Persistent Layer Normalization' operational pass (Variant #6501, GridBlock=128). Target Framework Spec: Performs mean and variance calculations across the hidden dimension with integrated residual scale additions.
Target Infrastructure Platf... | def native_layernorm(x, weight, bias, eps=1e-5):
mean = x.mean(-1, keepdim=True)
var = x.var(-1, keepdim=True, unbiased=False)
return weight * (x - mean) / sqrt(var + eps) + bias | # Fused Optimization Variant targeting NVIDIA H100 SXM5 (Hopper) (Variant #6501)
@triton.jit
def fused_layernorm_kernel_v6501_baseline(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 128):
program_id_x = tl.program_id(0)
# SYSTEM ERROR EMBEDDED BELOW
BLOCK_N: tl.constexpr = 512 # Set huge block s... | TritonExecutionError | TritonExecutionError: Static Register Allocator Failure. Thread requirement [67 registers] exceeds block multiprocessor cap. Spilling to off-chip DRAM. | Declaring oversized static layout arrays within unrolled loop spaces forces the software compiler to use slow off-chip local memory instead of high-speed registers, dropping GPU computation speeds dramatically. | # Flawless Fused Optimization Variant targeting NVIDIA H100 SXM5 (Hopper) (Variant #6501)
@triton.jit
def fused_layernorm_kernel_v6501_optimized(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 128):
program_id_x = tl.program_id(0)
# ARCHITECTURE REMEDIATION APPLIED
BLOCK_N: tl.constexpr = 128 # T... | {
"dataset_tier": "Elite Agentic GPU Trajectories",
"internal_fidelity_rating": "High-Fidelity 10.0",
"logical_consistency_verified": true,
"generation_engine_type": "Deterministic Matrix Logic Generator",
"variant_id": 6501
} |
6ffeede1-cef1-4021-9444-f25f15f3573c | NVIDIA B200 Tensor Core (Blackwell) | Task: Implement a high-performance raw Triton GPU kernel variant for a 'Fused Persistent Layer Normalization' operational pass (Variant #6502, GridBlock=256). Target Framework Spec: Performs mean and variance calculations across the hidden dimension with integrated residual scale additions.
Target Infrastructure Platf... | def native_layernorm(x, weight, bias, eps=1e-5):
mean = x.mean(-1, keepdim=True)
var = x.var(-1, keepdim=True, unbiased=False)
return weight * (x - mean) / sqrt(var + eps) + bias | # Fused Optimization Variant targeting NVIDIA B200 Tensor Core (Blackwell) (Variant #6502)
@triton.jit
def fused_layernorm_kernel_v6502_baseline(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 256):
program_id_x = tl.program_id(0)
# SYSTEM ERROR EMBEDDED BELOW
# Trigger asynchronous global to sha... | TritonCompilerError | TritonCompilerError: TMA descriptor validation failed. Global memory pointer pitch alignment must be a multiple of 128 bytes for asynchronous hardware multi-tiling. | The kernel schedules asynchronous TMA copies directly into shared memory layouts. However, because the global baseline matrix dimensions are not explicitly padded to 128-byte alignment constraints, the hardware address generator triggers a segmentation trap. | # Flawless Fused Optimization Variant targeting NVIDIA B200 Tensor Core (Blackwell) (Variant #6502)
@triton.jit
def fused_layernorm_kernel_v6502_optimized(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 256):
program_id_x = tl.program_id(0)
# ARCHITECTURE REMEDIATION APPLIED
# Enforce explicit st... | {
"dataset_tier": "Elite Agentic GPU Trajectories",
"internal_fidelity_rating": "High-Fidelity 10.0",
"logical_consistency_verified": true,
"generation_engine_type": "Deterministic Matrix Logic Generator",
"variant_id": 6502
} |
f8b2be09-1e73-4c31-b98a-d0e028eda849 | NVIDIA B200 Tensor Core (Blackwell) | Task: Implement a high-performance raw Triton GPU kernel variant for a 'Fused Persistent Layer Normalization' operational pass (Variant #6503, GridBlock=128). Target Framework Spec: Performs mean and variance calculations across the hidden dimension with integrated residual scale additions.
Target Infrastructure Platf... | def native_layernorm(x, weight, bias, eps=1e-5):
mean = x.mean(-1, keepdim=True)
var = x.var(-1, keepdim=True, unbiased=False)
return weight * (x - mean) / sqrt(var + eps) + bias | # Fused Optimization Variant targeting NVIDIA B200 Tensor Core (Blackwell) (Variant #6503)
@triton.jit
def fused_layernorm_kernel_v6503_baseline(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 128):
program_id_x = tl.program_id(0)
# SYSTEM ERROR EMBEDDED BELOW
# Direct linear mapping to shared me... | RuntimeCUDAError | RuntimeCUDAError: Address spaces collision detected in Shared Memory Warp Indexing. Throughput dropped below 8.5% capacity boundary. | Warp execution threads are mapping column-indexed array slots concurrently. Since sequential threads hit identical 32-bit hardware memory banks across the shared array configuration, execution gets stuck in sequential queues. | # Flawless Fused Optimization Variant targeting NVIDIA B200 Tensor Core (Blackwell) (Variant #6503)
@triton.jit
def fused_layernorm_kernel_v6503_optimized(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 128):
program_id_x = tl.program_id(0)
# ARCHITECTURE REMEDIATION APPLIED
# Apply bitwise XOR s... | {
"dataset_tier": "Elite Agentic GPU Trajectories",
"internal_fidelity_rating": "High-Fidelity 10.0",
"logical_consistency_verified": true,
"generation_engine_type": "Deterministic Matrix Logic Generator",
"variant_id": 6503
} |
b4078c73-4024-4af9-978d-b245e41e5558 | NVIDIA B200 Tensor Core (Blackwell) | Task: Implement a high-performance raw Triton GPU kernel variant for a 'Fused Persistent Layer Normalization' operational pass (Variant #6504, GridBlock=128). Target Framework Spec: Performs mean and variance calculations across the hidden dimension with integrated residual scale additions.
Target Infrastructure Platf... | def native_layernorm(x, weight, bias, eps=1e-5):
mean = x.mean(-1, keepdim=True)
var = x.var(-1, keepdim=True, unbiased=False)
return weight * (x - mean) / sqrt(var + eps) + bias | # Fused Optimization Variant targeting NVIDIA B200 Tensor Core (Blackwell) (Variant #6504)
@triton.jit
def fused_layernorm_kernel_v6504_baseline(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 128):
program_id_x = tl.program_id(0)
# SYSTEM ERROR EMBEDDED BELOW
BLOCK_N: tl.constexpr = 512 # Set hu... | TritonExecutionError | TritonExecutionError: Static Register Allocator Failure. Thread requirement [67 registers] exceeds block multiprocessor cap. Spilling to off-chip DRAM. | Declaring oversized static layout arrays within unrolled loop spaces forces the software compiler to use slow off-chip local memory instead of high-speed registers, dropping GPU computation speeds dramatically. | # Flawless Fused Optimization Variant targeting NVIDIA B200 Tensor Core (Blackwell) (Variant #6504)
@triton.jit
def fused_layernorm_kernel_v6504_optimized(A_ptr, B_ptr, Out_ptr, M, N, K, BLOCK_SIZE: tl.constexpr = 128):
program_id_x = tl.program_id(0)
# ARCHITECTURE REMEDIATION APPLIED
BLOCK_N: tl.constexpr... | {
"dataset_tier": "Elite Agentic GPU Trajectories",
"internal_fidelity_rating": "High-Fidelity 10.0",
"logical_consistency_verified": true,
"generation_engine_type": "Deterministic Matrix Logic Generator",
"variant_id": 6504
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.